Development of an Integrated High Energy Density

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DEVELOPMENT OF AN INTEGRATED HIGH ENERGY DENSITY

CAPTURE AND STORAGE SYSTEM FOR ULTRAFAST

SUPPLY/EXTENDED ENERGY CONSUMPTION APPLICATIONS

DRAGOS DINCA

Bachelor of Science in Electrical Engineering Cleveland State University May 2004

Master of Science in Electrical Engineering Cleveland State University December 2006

submitted in partial fulfillment of requirements for the degree

DOCTOR OF ENGINEERING

at the

CLEVELAND STATE UNIVERSITY

May 2017

We hereby approve the dissertation of Dragos Dinca

Candidate for the Doctor of Engineering degree. This dissertation has been approved for the specialization of Electrical and Computer Engineering

and CLEVELAND STATE UNIVERSITY’S College of Graduate Studies by

Hanz Richter, Dissertation Committee Chairperson – Department & Date

Taysir H. Nayfeh, Dissertation Committee Member – Department & Date

Lili Dong, Dissertation Committee Member – Department & Date

Majid Rashidi, Dissertation Committee Member – Department & Date

Petru S. Fodor, Dissertation Committee Member – Department & Date

April 27, 2017 Student’s Date of Defense

This student has fulfilled all requirements for the Doctor of Engineering degree.

Chandrasekhar Kothapalli, Doctoral Program Director

This accomplishment is dedicated to my family.

ACKNOWLEDGEMENTS

I would like to thank my adviser, Dr. Hanz Richter, for his guidance, advice, and support which helped me complete the work of this dissertation.

Thanks to Dr. Taysir Nayfeh, for the opportunity to work at the Industrial Space

Systems Laboratory (ISSL). The technical experience and business acumen gained at the

ISSL shaped my professional career.

I would like to thank the dissertation committee members for their service and guidance: Dr. Lili Dong, Dr. Majid Rashidi, and Dr. Petru Fodor.

Thanks to the colleagues at the NASA Glenn Research Center for their support:

Bob Scheidegger, Carol Tolbert, Tony Baez, Ray Beach, Jim Soeder, and Fred Wolf.

I would like to thank Dr. Daniel Raible for his guidance during this academic endeavor.

I would like to thank my colleagues at the ISSL for their camaraderie: David

Avanesian, Tom DePietro, Harry Olar, Andrew Jalics, Nick Tollis, Anita Wiederholt, Ishu

Pradhan, Brian Fast, Sagar Gadkari, Amanda Beach, Scott Darpel, Maciej Zborowski, and

Michael Wyban.

Special thanks to my wife, Ioana, for her unconditional love. And thanks to my brother, Daniel, and uncle, Victor, for believing in me.

My deepest appreciation goes to my parents, Viorica and Teofil, for their courage and sacrifice to offer our family better opportunities in a new world. Most of all, I would like to thank God for all blessings.

DEVELOPMENT OF AN INTEGRATED HIGH ENERGY DENSITY

CAPTURE AND STORAGE SYSTEM FOR ULTRAFAST

SUPPLY/EXTENDED ENERGY CONSUMPTION APPLICATIONS

DRAGOS DINCA

ABSTRACT

High Intensity Laser Power Beaming is a wireless power transmission technology

developed at the Industrial Space Systems Laboratory from 2005 through 2010, in

collaboration with the Air Force Research Laboratory to enable remote optical

‘refueling’ of airborne electric micro unmanned air vehicles. Continuous tracking of

these air vehicles with high intensity lasers while in-flight for tens of minutes to

recharge the on-board battery system is not operationally practical; hence the recharge

time must be minimized. This dissertation presents the development and system design

optimization of a hybrid electrical energy storage system as a solution to this practical

limitation. The solution is based on the development of a high energy density

integrated system to capture and store pulsed energy. The system makes use of

ultracapacitors to capture the energy at rapid charge rates, while lithium-ion batteries

provide the long-term energy density, in order to maximize the duration of operations

and minimize the mass requirements. A design tool employing a genetic algorithm

global optimizer was developed to select the front-end ultracapacitor elements. The simulation model and results demonstrate the feasibility of the solution. The hybrid energy storage system is also optimized at the system-level for maximum end-to-end power transfer efficiency. System response optimization results and corresponding sensitivity analysis results are presented. Lastly, the ultrafast supply/extended energy storage system is generalized for other applications such as high-power commercial, industrial, and aerospace applications.

TABLE OF CONTENTS

Page

ABSTRACT ...... v

LIST OF TABLES ...... xii

LIST OF FIGURES ...... xiii

NOMENCLATURE ...... xxi

CHAPTER

I. INTRODUCTION ...... 1

1.1 Dissertation Contributions and Organization ...... 7

II. BACKGROUND: HIGH INTENSITY LASER POWER BEAMING ...... 9

2.1 Wireless Power Transmission ...... 10

2.2 HILPB Enabling Technologies ...... 17

2.2.1 High Intensity VMJ Photovoltaic Cells ...... 18

2.2.2 High Intensity Lasers ...... 21

2.2.3 Directed Energy Systems ...... 22

2.2.4 HILPB Power Receiver ...... 27

2.3 HILPB: Author’s Contribution and Technology Status...... 29

2.3.1 HILPB Experimental Results – Optimal Operating Laser

Wavelength ...... 29

vii

2.3.2 High Power Laser Laboratory at CSU’s ISSL ...... 34

2.3.3 Current Status of the HILPB Technology ...... 36

III. ULTRAFAST ENERGY CAPTURE & HIGH ENERGY DENSITY

SYSTEM ...... 40

3.1 Electrical Energy Storage ...... 41

3.1.1 Battery Energy Storage ...... 46

3.1.2 Ultracapacitor Energy Storage ...... 50

3.2 Problem Definition, Objective, and Scope ...... 55

3.2.1 The Solution: Hybrid Energy Storage System ...... 55

3.3 Literature Review...... 57

3.3.1 Hybrid Battery-Ultracapacitor ESS in the Transportation

Industry ...... 58

3.3.2 Hybrid Battery-Ultracapacitor ESS in the Power Grid Industry ... 63

3.3.3 Ultracapacitor Applications...... 66

3.3.4 Summary of Findings and Conclusion ...... 67

IV. POWER SYSTEM DESIGN AND DEVELOPMENT IN SUPPORT OF

HILPB ...... 71

4.1 1st Generation HILPB End-to-End Power System ...... 71

4.2 2nd Generation HILPB End-to-End Power System ...... 79

4.3 Power Management and Distribution for the FQM-151A Aircraft ...... 85

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4.3.1 Battery Charging and Control Subsystem ...... 87

4.3.2 Control and Data Handling Subsystem ...... 89

4.3.3 Integration into the FQM-151A Pointer Aircraft ...... 91

V. SYSTEM MODELING, SIMULATON, AND DESIGN OPTIMIZATION .... 94

5.1 Requirement Definition for the Energy Storage System On-Board the

MUAV ...... 95

5.2 Development of an Optimization Routine for the Energy Capture

Elements ...... 101

5.2.1 Objective Function Derivation ...... 101

5.2.2 Formulating the Objective Function ...... 108

5.2.3 Implementation of the Optimization Routine...... 111

5.2.4 Optimization Results using Genetic Algorithms ...... 113

5.3 Model Development, Simulation, and Duty Cycle Optimization ...... 117

5.3.1 Simulation Environment and Component Models ...... 117

5.3.2 Modeling and Simulation Results ...... 120

5.3.3 Intermittent Optical Energy Transmission: Duty Cycle

Optimization ...... 125

5.4 System Optimization for Maximum End-to-End Power Transfer

Efficiency ...... 133

5.4.1 System Design Optimization ...... 134

5.4.2 Genetic Algorithm Optimization of the Energy Capture

Elements ...... 136

5.4.3 System Response Optimization ...... 140

5.4.4 Sensitivity Analysis ...... 145

VI. TECHNOLOGY INFUSION AND APPLICATIONS ...... 153

6.1 Generalization and Scalability to other Applications ...... 153

6.2 Civilian Space Applications ...... 155

6.2.1 Supplemental Power for Satellites ...... 156

6.2.2 Power for Lunar and Deep Space Exploration Assets ...... 159

6.3 Department of Defense (DoD) Applications ...... 162

6.3.1 DoD Space Applications ...... 162

6.3.2 DoD Terrestrial Applications ...... 166

6.4 Commercial Terrestrial Applications ...... 172

6.4.1 Hybrid-Electric and Turbo-Electric Aircraft Applications ...... 172

6.4.2 Rapid Charge Applications ...... 175

VII. CONCLUSIONS AND FUTURE WORK ...... 179

7.1 Future Work ...... 182

REFERENCES ...... 184

APPENDICES ...... 197

APPENDIX A: OBJECTVE FUNCTION IMPLEMENTATION IN MATLAB

(MAIN RUN FILE) ...... 198

APPENDIX B: OBJECTVE FUNCTION IMPLEMENTATION IN MATLAB ... 200

APPENDIX C: OBJECTVE FUNCTION CONSTRAINTS IMPLEMENTATION

IN MATLAB...... 201

APPENDIX D: COPYRIGHT PERMISSIONS ...... 202

LIST OF TABLES

Table Page

Table I: Classification of WPT Methods ...... 10

Table II: Test Results Using The 808 nm Wavelength Laser System [5] ...... 31

Table III: Test Results Using The 940 nm Wavelength Laser System [5] ...... 32

Table IV: Test Results Using The 976 nm Wavelength Laser System [5] ...... 32

Table V: Summary of HILPB Test Results – Peak Power Density ...... 38

Table VI: Comparison of Electrical Energy Storage Technologies ...... 45

Table VII: Comparison of the State-of-the-Art Lithium-Ion Batteries and

Ultracapacitors ...... 54

Table VIII: Industry, Market Domain, and Applications Of Ultracapacitors ...... 69

Table IX: FQM-151A Pointer Aircraft Specification [106] ...... 86

Table X: Power Consumption Data for the Raven UAV during Increasing and

Decreasing Throttle Positions [116] ...... 99

Table XI: Database of Available Ultracapacitors ...... 112

Table XII: Optimization Results using The Genetic Algorithm Optimizer ...... 116

Table XIII: Summary Of Potential Applications ...... 154

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LIST OF FIGURES

Figure Page

Figure 1: a) Knochenhauer Spirals [18]; b) Hertz’s WPT Apparatus ...... 11

Figure 2: Nikola Tesla Experimenting with a 200-ft Tesla Coil, which ...... 12

Figure 3: Diagram of the Microwave-Powered Helicopter [26] ...... 13

Figure 4: MHI’s High-Power MPT Transmitter (left) and Receiver (right) ...... 14

Figure 5: Diagram of the Experimental Setup ...... 15

Figure 6: Laser Power Beaming to a MUAV at NASA MSFC [31] ...... 16

Figure 7: Diagram of Laser Beam Director and Tracking System ...... 17

2 Figure 8: High-Intensity Silicon VMJ Solar Cell (40 junctions, 0.78 cm ) ...... 19

Figure 9: Spectral Response of a Typical VMJ Solar Cell ...... 20

Figure 10: VMJ Solar Cell I-V Curves for 100 to 2500 Sun Intensities – Tests

Conducted at NASA GRC’s LAPSS ...... 21

Figure 11: Arhimedes’ Flaming Death Ray [42]. Artist credit: Grace Smith...... 23

Figure 12: History of Research and Development in Directed Energy Weapons ...... 24

Figure 13: Potential Applications for the Joint High Power Solid-State Laser ...... 25

Figure 14: High-Energy Laser Mobile Demonstrators by Lockheed Martin (left) .... 27

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Figure 15: Air-Cooled and Water-Cooled HILPB Power Receivers Built by the

ISSL Team [3-8] ...... 28

Figure 16: LIMO 350 Watts Solid-State Fiber-Coupled Diode Laser System ...... 30

Figure 17: Hardware Set-up for the Frequency Optimization Tests with Beam

Homogenization Optics at Limo’s Laser Facility in Dortmund, Germany ...... 31

Figure 18: Maximum Output Power for Each Wavelength Laser System [5] ...... 33

Figure 19: Conversion Efficiencies for all Wavelengths Laser Systems [5] ...... 34

Figure 20: Optical Input vs Electrical Output for All Wavelength

Laser Systems [5] ...... 34

Figure 21: ISSL’s High-Power Laser Laboratory at CSU (Front View)...... 35

Figure 22: ISSL’s High-Power Laser Laboratory at CSU (Laser System View) ...... 36

Figure 23: Peak Power Density Experiment – Single VMJ Cell with Gaussian Laser

Beam (Water and Air Cooling) ...... 38

Figure 24: Peak Power Density Experiment – HILPB 9-Cell Parallel Array Receiver with Gaussian Laser Beam (Air Cooling) ...... 39

Figure 25: Peak Power Density Experiment – HILPB 9-Cell Parallel Array Receiver with Uniformed Laser Beam (Flat-Top Optics and Water Cooling) ...... 39

Figure 26: Electrical Energy Storage Systems and Technologies ...... 42

Figure 27: Ragone Plot of Various Electrical Energy Storage Technologies with

Charge Time Durations ...... 43

Figure 28: Flywheel Energy Storage System ...... 44

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Figure 29: Comparison of Recharge Time Duration for Various Electrical Energy

Storage Technologies ...... 46

Figure 30: Battery – Basic Elements and Operation ...... 47

Figure 31: Rechargeable Battery Systems – Energy Storage Capabilities ...... 48

Figure 32: Li-ion Battery – Basic Elements and Operation...... 49

Figure 33: Discovery of the Leyden jar in 1746 ...... 51

Figure 34: Classification of Capacitor Technologies ...... 52

Figure 35: Evolution of the Ultracapacitor Technology...... 53

Figure 36: Proposed Ultrafast Capture and High Electric Energy Density

Storage System...... 56

Figure 37: Block Diagram of Proposed Ultrafast Energy Capture and High Electric

Energy Density Storage System...... 57

Figure 38: Top 5 Markets for Ultracapacitors-Based Energy Storage Systems ...... 58

Figure 39: Pictorial Depiction of Ultracapacitors in Regenerative Braking Systems

[90]. Courtesy of Maxwell Technologies, Inc. Used with permission, Appendix D...... 60

Figure 40: Pictorial Depiction of Hybrid Ultracapacitors and Batteries in Engine

Start Systems [92]...... 61

Figure 41: Pictorial Depiction of Proposed Charging Station for Electric Vehicles .. 63

Figure 42: Pictorial Depiction of the Electrical Power Grid. Adapted from [93]. .... 64

Figure 43: Application Model of Ultracapacitor Hybrid Energy Storage Systems.

Reprinted from [81]. Used with permission, Appendix D...... 70

Figure 44: 1st Generation End-to-End Power System Design in Support of HILPB . 72

Figure 45: Circuit Design – Voltage and Current Measurement ...... 74

Figure 46: HILPB Power System – Block Diagram of the Battery Charging and

Power Management within the Energy Storage Subsystem ...... 77

Figure 47: HILPB Power System – Final Hardware Implementation ...... 78

Figure 48: HILPB Power System – Energy Storage Subsystem ...... 79

Figure 49: 2nd Generation HILPB End-to-End Power System ...... 80

Figure 50: Actively Regulated Electronic Load for Photovoltaic Applications (I-V

Characteristic Curve Generation) ...... 81

Figure 51: 2nd Generation HILPB Power System – Block Diagram of the Sensing

Electronics and Overall System Functionality ...... 82

Figure 52: 2nd Generation HILPB End-to-End Power System Hardware ...... 84

Figure 53: FQM-151A Pointer Airplane during Military Operations ...... 86

Figure 54: Battery Charging Circuitry – MAXIM1535DEVKIT ...... 88

Figure 55: dsPICDEM 1.1 Plus Development Board and Additional

Interface Hardware ...... 89

Figure 56: Power Management and Distribution Subsystem’s Hardware Interface .. 90

Figure 57: The Control and Data Handling (C&DH) Subsystem’s Interface ...... 91

xvi

Figure 58: HILPB Power Receiver Installed into the FQM-151A

Pointer Aircraft [2, 3] ...... 92

Figure 59: HILPB Research and Development Tests with the Pointer Aircraft at the

CSU’s ISSL High Intensity Laser Laboratory ...... 93

Figure 60: HILPB Testing Set-Up using the HILPB End-to-End Power System,

Electronic Load, Personal Computer, Aircraft Gimbal System, and Laser System ...... 93

Figure 61: Raven® RQ-11B MUAV. Courtesy of AeroVironment, Inc. (Used with permission, Appendix D)...... 96

Figure 62: Raven® RQ-11B Battery Endurance Tests – Voltage

Measurements [116]...... 99

Figure 63: Raven® RQ-11B Battery Endurance Tests – Amperage

Measurements [116]...... 100

Figure 64: User-Interactive Optimization Routine via the Matlab

Command Window ...... 115

Figure 65: Optimization Routine Convergence Plot During the GA Optimization . 115

Figure 66: Modifications to the Ultracapacitor Model for Use with

Simscape Electronics ...... 119

Figure 67: Ultracapacitor Model for Simscape Electronics –

Parameters and Options ...... 119

Figure 68: Implementation of the Ultrafast Energy Capture and High Energy

Density Storage System for HILPB Applications from Figure 37 ...... 121

xvii

Figure 69: Simulation Model of the Ultrafast Energy Capture and High Energy

Density Storage System Utilizing 2xDC/DC Converters ...... 122

Figure 70: Ultracapacitor Low Discharge Protection Circuit...... 122

Figure 71: Simulation Results of the Ultrafast Energy Capture and High Energy

Density Storage System Utilizing 2xDC/DC Converters – Input Energy Source and

Ultracapacitor Bank ...... 124

Figure 72: Simulation Results of the Ultrafast Energy Capture and High Energy

Density Storage System Utilizing 2xDC/DC Converters – Battery and Load ...... 125

Figure 73: Simulation Model of the Ultrafast Energy Capture and High Energy

Density Storage System for HILPB Applications Configured for the SDO ...... 127

Figure 74: Optimization Requirements – Converting Design

Variables into Signals ...... 127

Figure 75: Mission Profile Implementation for the RQ-11B Raven ...... 128

Figure 76: Duty Cycle Optimization of Intermitted Laser Beam – Objective

Function Definition ...... 129

Figure 77: Initial Conditions and Signal Requirements Settings for the Simulink

Design Optimization ...... 130

Figure 78: SDO Simulation Results with the Gradient Descent Method ...... 130

Figure 79: SDO Simulation Results – Optimization Progress Report ...... 131

Figure 80: Simulation Results with the SDO’s Optimum Duty Cycle – Input Energy

Source and Ultracapacitor Bank ...... 132

xviii

Figure 81: Simulation Results with the SDO’s Optimum Duty Cycle –

Battery and Load ...... 133

Figure 82: Hybrid ESS for HILPB Applications – Option #2 (One DC/DC

Converter Used for the Transfer of Electrical Energy On-Board the MUAV) ...... 135

Figure 83: Simulation Model of the Modified Ultrafast Energy Capture and High

Energy Density Storage System for HILPB Applications Configured for the SDO ...... 136

Figure 84: GA Optimization Results – Optimization Progression ...... 139

Figure 85: GA Optimization Results – Matlab Command Window ...... 139

Figure 86: Design Variables with Initial Conditions ...... 142

Figure 87: Optimization Cost Functions ...... 142

Figure 88: SDO Response Optimization Method and Options ...... 142

Figure 89: System Design Optimization Results...... 143

Figure 90: System Design Optimization Results – Optimization Progress Report .. 143

Figure 91: Simulation Results 1xDC/DC Converter and SDO’s Optimum Duty

Cycle and Input Current Limit – Input Energy Source and Ultracapacitor Bank ...... 144

Figure 92: Simulation Results 1xDC/DC Converter and SDO’s Optimum Duty

Cycle and Input Current Limit – Battery and Load ...... 145

Figure 93: Exporting Optimization Cost Functions and Design Variables from the

SDO Response Optimization to the SDO Sensitivity Analysis ...... 147

Figure 94: Sample Design Space Generation for Each Parameter ...... 148

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Figure 95: Visualization of the Sample Design Space for Each Parameter ...... 148

Figure 96: Sensitivity Analysis Evaluation Results – Cost Function Distribution for

Each Design Variable ...... 150

Figure 97: Sensitivity Analysis – Contour Plots of Evaluation Results ...... 151

Figure 98: Sensitivity Analysis – Statistics Evaluation Methods ...... 152

Figure 99: Configurations of the ultrafast energy capture and high electrical energy density storage system for Optical, Electrical, and Magnetic Energy Sources ...... 155

Figure 100: Extending Battery and Satellite Life via Intermittent HILPB [125] ...... 158

Figure 101: NASA Proposed Laser Power Beaming Demo – ISS to FalconSATs ...... 159

Figure 102: Lunar Assets (credit: Anna Nesterova; Bryan Versteeg, spacehabs.com) . 160

Figure 103: System F6 – Pictorial Illustration [131] ...... 163

Figure 104: System F6 – Wireless Data & Power Transfer [130, 133] ...... 163

Figure 105: Space-Based Solar Power – Energy Resource Opportunity [137] ...... 165

Figure 106: Space-Based Solar Power – Laser Power Beaming to Earth (credit: Graham

Murdoch, mmdi.co.uk). Used with permission, Appendix D...... 166

Figure 107: High Altitude Airship – Stratobus (Courtesy of Thales Alenia Space) ...... 170

Figure 108: eConcept – Hybrid-Electric Airliner (Courtesy of Airbus Group) ...... 173

Figure 109: E-Thrust – Serial Hybrid-Electrical Distributed Propulsion System [147]

(Courtesy of Airbus Group) ...... 175

Figure 110: Battery Pack for Tesla Model S – Individual AA Li-ion Battery Cells ...... 177

NOMENCLATURE

ABL: Airborne Laser

AC: Alternative Current

AFB: Air Force Base

AFRL: Air Force Research Laboratory

AFRC: Armstrong Flight Research Center

C&DH: Command and Data Handling

CSU: Cleveland State University

DARPA: Defense Advanced Research Projects Agency

DC: Direct Current

DEW: Directed Energy Weapons

DoD: Department of Defense

DPAL: Diode Pumped Alkali Vapor Based Laser

EDLC: Electrochemical Double-Layer Capacitors

ESR: Equivalent Series Resistance

EV: Electric Vehicle

FES: Flywheel Energy Storage

FOB: Forward Operating Base

xxi

FPGA: Field Programmable Gate Array

GA: Genetic Algorithm

GEO: Geosynchronous Earth Orbit

GRC: Glenn Research Center

GUI: Graphical User Interface

HILPB: High Intensity Laser Power Beaming

IC: Integrated Circuit

IEEE: The Institute of Electrical and Electronic Engineers

ISSL: Industrial Space Systems Lab

JAXA: Japan Aerospace Exploration Agency

JHPSSL: Joint High Power Solid State Laser

LAPSS: Large Area Pulsed Solar Simulator

LCD: Liquid Crystal Display

LEO: Low Earth Orbit

Li: Lithium

LIMO: Lissotschenko Mikrooptik GmbH

MSFC: Marshall Space Flight Center

MIT: Massachusetts Institute of Technology

MHI: Mitsubishi Heavy Industries

xxii

MOSFET: Metal-Oxide-Semiconductor Field-Effect Transistor

MPT: Microwave Power Transmission

MUAV: Micro Unmanned Air Vehicle

NASA: National Aeronautics and Space Administration

PCB: Printed Circuit Board

PMAD: Power Management and Distribution

RF: Radio Frequency

SBSP: Space-Based Solar Power

SDO: Simulink Design Optimization

SMES: Superconducting Magnetic Energy Storage

SOC: State of Charge

TRL: Technology Readiness Level

UAV: Unmanned Air Vehicle

UPS: Uninterruptable Power Supply

W: Watt

VMJ: Vertical Multi Junction

WPT: Wireless Power Transmission

xxiii

CHAPTER I

INTRODUCTION

This dissertation offers a solution to the practical limitation of using the High

Intensity Laser Power Beaming (HILPB) technology [1, 2, 3, 4, 5, 6, 7, 8] for in-flight remote optical ‘refueling’ of electric micro unmanned air vehicles (MUAV). The solution is based on the development of a high energy density integrated system to capture and store pulsed energy. The system makes use of the ultracapacitor technology to capture the electrical energy at rapid rates, while Lithium-ion batteries provide the energy density.

Using these technologies in a hybrid configuration will enable a variety of applications that require high-speed (rapid rate) intermittent high energy pulses of short duration and extended energy consumption.

Electrical energy storage systems are ever present in our daily life; from mobile electronic devices, transportation and communication systems, to electric power generation and transmission, there are countless applications that require a means of delivering, storing, and managing electrical energy. Recent technological advances are pushing the boundaries of such systems as new applications requiring portable power, demand that

energy be transferred and stored from the power source to the end-user at ideally instantaneous rates.

One such application, which is the motivation of this dissertation, is that of delivering electrical energy via a high intensity laser to a remote airborne MUAV. The Air

Force Research Laboratory (AFRL) has been looking to develop an “Airborne, Integrated

Surveillance and Close Operations Support System”, which consists of a fleet of all-electric

MUAVs that have the capability of being refueled in-flight and can be deployed from high altitude airships, in order to provide a 24/7 aerial dominance of the theater of operations via constellations of MUAVs. The drive behind this military objective is a push from the

Department of Defense (DoD) to reduce operational cost by extending the mission duration of MUAVs via further advancement of unmanned air systems. DoD’s “Unmanned Systems

Integrated Roadmap FY2013-2038” outlines the need to advance technologies in the area of alternative energy sources and power systems in order to expand the flight range limitation of current unmanned air systems [9] (the “Unmanned Systems Integrated

Roadmap FY2016-2041” will be released in 2017). Furthermore, in 2015 the National

Aeronautics and Space Administration (NASA) solicited proposals for space technology development and demonstration of five technology topic areas; one of the primary technology areas called for private-public partnership with NASA was to develop and demonstrate optical and radio frequency (RF) wireless power transfer technologies [10].

To this end, under a contract from AFRL’s Revolutionary Munitions Directorate at

Eglin Air Force Base (AFB), the Industrial Space Systems Laboratory (ISSL) at Cleveland

State University (CSU) has developed the HILPB technology, which enabled AFRL to move closer to meeting its program objective, i.e. “Airborne, Integrated Surveillance and

Close Operations Support System”. The key technological requirement and the drive behind this program is that of prolonging the aircraft flight time, by ‘refueling’ the all- electric MUAV in mid-air instead of having it return to its base. Furthermore, this technology dramatically reduces the logistics burden on the forward-deployed war-fighter in having to carry and exchange the battery packs in the field. The HILPB technology developed at the ISSL is a form of wireless power transmission for space and terrestrial applications, developed specifically to deliver long range optical ‘refueling’ of electric platforms such as the all-electric MUAV and other resource constrained vehicles [1-8].

The in-flight optical ‘refueling’ of the electric MUAV would be accomplished by making use of the HILPB technology, where a high intensity laser is used to transmit electrical energy to the aircraft. On the receiving end, the MAUV is equipped with a

HILPB receiver specially designed to absorb high intensity optical energy and convert it into electrical power. One of the advantages of the HILPB technology is that the MUAV is not constrained to a single source of transmitted energy, as there are different platforms that can support high intensity lasers (airships, ground locations, satellites, and other far- away feasible support systems).

One of the limiting factors of using the HILPB technology for in-air long range laser ‘refueling’ of MUAVs is the energy storage system on-board the aircraft, which limits the MUAV’s payload, flight duration, and range. Currently, Lithium polymer (Li-poly) batteries are used on-board the MUAV to store the electrical energy used for propulsion and overall aircraft functionality. Li-poly batteries limit the flight duration of the MUAV to 60-to-90 minutes, depending on weather conditions. Once the electric energy is consumed, the MUAV returns to base or a waypoint so that its on-board battery is replaced

or re-charged. The recommended charge time for Li-poly batteries, as recommend by the battery manufacturers, is 60 minutes or more. It is possible to increase the battery charge rate, but additional amperage flow through the battery will have a negative impact on the lifetime and capacity of the battery pack.

The HILPB technology plays a major role in achieving AFRL program’s objective of 24/7 surveillance by charging the on-board battery using a high intensity laser via remote optical ‘‘refueling’’ of the electric MUAV. However, tracking the MUAV with a high intensity laser continuously for tens of minutes, in order to recharge the on-board battery system, is not operationally practical. It follows that the development of an electrical energy storage system that can drastically reduce the optical re-fueling time of an electric

MUAV is imperative.

Therefore, this dissertation embarked on the task of developing a portable electrical energy storage system that is able to absorb, transfer, and store large amounts of electrical energy at extremely fast rates, i.e. tens of seconds, while still maintaining a high energy density, within the weight and size constraints of the MUAV. This will be a key technological advancement towards the realization of AFRL’s “Airborne, Integrated

Surveillance and Close Operations Support System”, as it will take the program to a higher

Technology Readiness Level (TRL) by making it more feasible, practical, and cost- effective.

Implementing such an energy storage system on-board the MUAV will enhance and expand the capability of not just the aircraft alone, but also of the entire battle group.

Beaming power to an aircraft that is capable of capturing and storing the electric energy at rapid rates will result in increased surveillance capability as the MUAV will not need to be

in permanent contact with the energy source; in contrast, it will search for an energy signal of opportunity that is of short duration in order to re-fuel in mid-air. As a consequence, the number of MUAVs that can be re-fueled with the same number of optical energy sources (high intensity lasers) can be significantly increased. Moreover, since less time is required to re-fuel, the aircraft will not need to fly in close proximity to the energy source, which means that the aircraft detection by non-friendly forces will be minimized. Lastly, a perpetual flying UAV will be of great importance to many other military and civilian applications.

The proposed energy storage system along with the HILPB technology will enable applications that would make use of the novel concept presented in this dissertation: optical

‘refueling’ of electric platforms (MUAVs, satellites, robots, high altitude airships, etc.) via intermittent beamed laser power. For example, applications that will benefit from increased mission endurance and exploration capability include robotic exploration missions, deep space exploration, and high altitude airships. For space exploration applications, generating power locally (on-board the spacecraft or rover) continues to be a technological challenge for NASA as demonstrated by the solicitation for space technology development that was released to the general public in 2015 [10]. The challenges associated with the on-board power generation system consists of mass penalties, cost increase for missions, and even mission viability. To address these challenges, NASA seeks to develop and validate wireless power transfer capabilities between various terrestrial and space assets. To this end, the following applications for wireless power transfer are being considered for space exploration applications: “in-space power beaming between orbiting spacecraft, power beaming from an in-space orbiting spacecraft to a

planetary asset, and power beaming between mobile assets on the surface of a planetary body” [10]. Other similar applications include beaming power to satellites, lunar habitats, and other terrestrial and space power plants that would make use of intermitted beamed optical power. Moreover, this energy storage system will enable the development of an integrated optical communication and power system, which enables optical communication and intermittent power transfer via a single channel/system of intermittent beamed laser power.

The proposed energy storage system can be used in other applications that require fast electrical energy capture, transfer, and storage. For example, such a system may be used in electric vehicles to considerably reduce the wait-time needed to re-charge an electric vehicle. Currently, electric vehicles require hours to fully re-charge; one can only wonder how the market for electric vehicles may change if the time required to re-charge an EV is reduced from hours to minutes.

In addition, such an energy storage system may find its use in other transportation systems, and a variety of other similar applications. One futuristic concept that may be enabled by this technology is related to electric vehicles. The idea is to design and implement an energy lane within a regular highway so that electric vehicles may be re- charged while in motion; whenever the vehicle needs to re-fuel, the vehicle may be driven over the energy lane. By implementing the energy storage system addressed in this dissertation, the electric vehicle will be able to capture and store the intermittent high energy pulses, and thus be able to re-charge quickly and while in motion. Adding a radio frequency (RF) identity tag to the vehicle, the driver can be billed automatically for the energy usage, thus eliminating the need to re-fuel overnight or at fuel stations, saving time

and adding convenience. This concept can also be applied towards transit trains, and other related transportation systems and applications.

1.1 Dissertation Contributions and Organization

The author of this dissertation has been an integral member of the ISSL team during the entire development cycle of the HILPB technology, for a period of five years. The scientific publications pertaining to the development of the HILPB technology are outlined in [2-6]. Chapter II summarizes the development of the HILPB technology, where Section

2.3.1 outlines one of the author’s significant contributions – the experimental results performed in Germany to determine the optimal operating wavelength of the laser system with the VMJ cell. Chapter III defines the problem, outlines the proposed solution, and presents the pertinent literature review. The power management and distribution (PMAD) system designed to be integrated into the all-electric MUAV is detailed in Chapter IV,

Section 4.3. Since this PMAD system was derived from the power systems previously designed by the author of this dissertation to support the research and development efforts of the HILPB technology, Section 4.1 and Section 4.2 outline the detailed designs of these power systems.

Chapter V is composed of four main subsections: the requirements for the energy storage system on-board the MUAV are defined in Section 5.1; an optimization routine is developed in Section 5.2 to be implemented as a design tool for the front-end energy storage elements used to capture the high energy pulses; the proposed energy storage

system on-board the MUAV is modeled and simulated in Section 5.3; the system is further optimized, in Section 5.4, to achieve maximum end-to-end power transfer efficiency, where the system response optimization results and corresponding sensitivity analysis results are presented in Section 5.4.3 and Section 5.4.4 respectively. In Chapter VI, the ultrafast energy capture and high electrical energy density storage system is generalized and scaled to enable applications that may not be feasible without the use of this energy storage solution. The conclusions and future work are presented in Chapter VII.

CHAPTER II

BACKGROUND: HIGH INTENSITY LASER POWER BEAMING

The motivation for developing the HILPB technology was to support one of

AFRL’s mission objectives of achieving 24/7 aerial dominance of the theater of operations via a fleet of all-electric MUAVs, which are re-fueled remotely, while in-flight, using a high intensity laser. The goal of the HILPB technology is to eliminate the constraints caused by the limited electric fuel capacity on-board MUAVs. The aircraft’s ability to gather intelligence for sustained periods of time is constrained by the flight duration of its missions. In order to increase the MUAV’s flight time, the electric capacity of the fuel tank must also be increased. Increasing the size of the fuel tank adds unwanted weight to the aircraft, which could make the aircraft less maneuverable and thus more vulnerable to enemy detection. Hence, the HILPB technology was designed to offer a feasible and cost effective alternative to these aircraft constraints and mission limitations, by ‘refueling’ the all-electric UAV while in mid-air and from far away distances. The novel HILPB system developed at the ISSL is an optical point-to-point wireless power transmission system, which is also capable of optical communication.

2.1 Wireless Power Transmission

The HILPB technology makes use of the concept of wireless power transmission

(WPT), which is defined in [11] as the “process of transmitting electrical energy from the power source to the load without using any wires for connection”. WPT is divided into two major categories: near-field and far-field. Near-field WPT is accomplished using inductive, magnetic, and electrostatic coupling methods; far-field WPT is achieved using lasers, microwaves, and radio-waves to transmit power over very large distances. Table I illustrates the classification of WPT methods.

TABLE I: CLASSIFICATION OF WPT METHODS [11, 12, 13, 14]

From a historical perspective, the process of developing WPT began with the discovery of generating magnetic fields using electrical currents by André-Marie Ampère in 1820. Subsequent discoveries by Michael Faraday (electromagnetic induction in 1831),

James Mawell (mathematical model of electromagnetic radiation in 1864), Oliver

Heaviside (re-formulated Maxwell’s equations) paved the way for Heinrich Hertz as the first person to demonstrate WPT in 1886 [15]. Hertz performed research on electromagnetic induction in an effort to demonstrate Maxwell’s prediction in electromagnetic wave theory via hardware tests. During his research, Hertz observed that discharging a Leyden jar into a Knochenhauer spiral produces a spark in the adjacent coil.

Hertz used this observation to build an apparatus, which generated and detected high- frequency power waves of the same power amplitude (in the range of mega Hz) – this historic event of high frequency WPT is also known as the discovery of radio waves [16,

17, 18].

a) b)

Figure 1: a) Knochenhauer Spirals [18]; b) Hertz’s WPT Apparatus

At the end of the nineteenth century, Nicola Tesla used Hertz’s concepts in high frequency electromagnetic induction to pioneer long distance wired power transfer and wireless power transfer. Tesla changed the world by winning the battle with Thomas

Edison in wired electric energy transmission, by demonstrating the effectiveness of transmitting electric energy over long distances through conducting wires using alternative current (AC) instead of Edison’s direct current (DC). Wired electric energy transmission in today’s world is achieved using Tesla’s concepts of AC power grids in part due to the benefits of lower conductor losses. Tesla’s vision was to use AC to distribute electric energy around the world wirelessly. To this end, Tesla’s fascination with high-frequency alternative currents and magnetic resonance led him to invent the Tesla coil [19] and subsequently to demonstrate wireless transmission of electric energy in various laboratory settings. Tesla also demonstrated wireless illumination of phosphorescent and incandescent lamps during various presentations in the United States and Europe [20, 21,

22, 23].

Figure 2: Nikola Tesla Experimenting with a 200-ft Tesla Coil, which

Resonated 300 kW at 150 Hz [24]

The next major event in the field of WPT occurred in the 1930s, when H. V. Noble at the Westinghouse Laboratory replicated some of Tesla’s WPT experiments. Several other developments occurred during that decade in the field of WPT, including the development of the radar in the 1940s during World War II, which led to significant improvements in the microwave generation technology. During the late 1950s, the development of the high-power microwave tube amplifier led to renewed interest in the area of microwave power transmission (MPT), which is another form of WPT. In 1960,

William Brown which is considered the pioneer in MPT, developed high-power rectifiers which made MPT possible and practical [15]. In 1963, MPT was successfully demonstrated in a laboratory environment by the Raytheon Company, under the direction of William Brown, where a few hundred watts were transmitted over 25 feet at 2450 MHz

[25]. A year later, the Raytheon Company also demonstrated a microwave-powered helicopter where a beam of microwave energy was used to power a 3 kg helicopter, while in flight, for approximately 10 hours. The basic elements of the microwaved-powered helicopter are illustrated in Figure 3 [26].

Figure 3: Diagram of the Microwave-Powered Helicopter [26]

Since the first MPT demonstration in the 1960s, the technology evolved over time as high power, longer distances, and higher overall system efficiencies were achieved.

MPT technology was also developed internationally by Japan and Canada. Japan has been interested in the MPT technology due to the limited natural energy resources available.

Specifically, Japan is interested in the application of MPT to space solar power as the Japan

Aerospace Exploration Agency (JAXA) aims to beam 1 gigawatt of solar power to Earth in the 2030s. To this end, the state of the art in MPT was achieved in 2015 when Mitsubishi

Heavy Industries (MHI) successfully demonstrated 10 kW of terrestrial MPT covering a distance of 500 meters; the receiver aperture is shown in Figure 4 [27]. Other MPT applications include: telecommunications, terrestrial aircraft propulsion, and lower-Earth orbit transportation systems [28]. In some systems, MPT couples communication and power transmission into a single link, thus enabling a variety of space applications.

Although MPT can achieve high efficiencies, its wavelengths diffract over long distances.

Large receiver apertures must be used in order to account for the wavelength diffraction, which in turn limits the application realm of this technology.

Figure 4: MHI’s High-Power MPT Transmitter (left) and Receiver (right) Apertures

[27]. Courtesy of Mitsubishi Heavy Industries, Ltd. (Used with permission, Appendix D)

Besides MPT, another advance in the realm of WPT was achieved in 2006 by a team from the Massachusetts Institute of Technology (MIT). The team led by Marin

Soljacic used magnetic resonance concepts, originally developed by Nikola Tesla, to transfer 60 Watts over a distance of two meters with an efficiency of 40 % by making use of near-field magnetic resonant induction at mega-hertz frequencies. The power levels at

these frequencies, however, may exceed the safety standards. The technology was developed for portable electronic devices such as mobile phones, laptops, etc. [15, 29].

Figure 5: Diagram of the Experimental Setup. Reprinted from [29]. Used with

permission, Appendix D.

Aside from microwave power beaming, another technology suited for WPT is the wireless transmission of laser energy, also known as laser power beaming. The first demonstrations of laser beaming power to a MUAV occurred at NASA’s Marshall Space

Flight Center (MSFC) and Armstrong Flight Research Center (AFRC) in 2002 and 2003.

During these experiments, a 1.5 kW 940 nm diode array laser was used to beam power to a MUAV, which was equipped with a photovoltaic array as shown in Figure 6. The laser beam had an irradiance of 560 W/m^2, which delivered 40 Watts of radiant energy to the photovoltaic array and consequently 7 W of electric energy to the MUAV propeller [30,

31, 32].

Figure 6: Laser Power Beaming to a MUAV at NASA MSFC [31]

In 2010, LaserMotive Inc. and Ascending Technologies demonstrated the continuous operation of a quadcopter MUAV for 12 hours while powered by a 1 kW diode array laser. The MUAV was equipped with a photovoltaic receiver, which was build using dual-junction gallium arsenide photovoltaic cells manufactured by Spectrolab. Since the nominal voltage of one solar cell was 2.1 Vdc, two strings of eight cells were required to produce a receiver voltage of 13.6 Vdc. The downside of this configuration resulted in an oversized receiver as the laser beam irradiance onto the photovoltaic receiver was 15 cm x

15 cm. The electric MUAV was automatically tracked during the duration of the flight by the laser control gimbal with an accuracy of ± 15 ⁰; a diagram of the laser power beaming system is depicted in Figure 7. The total weight of the MUAV was approximately 1.1 kg

[33, 34].

Figure 7: Diagram of Laser Beam Director and Tracking System. Reproduced from

2.2 HILPB Enabling Technologies

High intensity laser power beaming is a form of WPT. This technology was developed at CSU’s ISSL for terrestrial and space applications – it makes use of high intensity lasers to focus and deliver extremely high intensity laser light onto a small photovoltaic power receiver, which converts the laser light into electric energy at high efficiencies. The demonstrated efficiency of the HILPB technology at the photovoltaic- array power receiver, via continuous conversion of high intensity optical energy at infrared wavelengths into electrical energy, was approximately 44%; the demonstrated power density was approximately 20 푊/푐푚2 [3, 4, 8]. Advances in lasers and photovoltaic

devices have enabled the development of the HILPB system; the necessary background information of these enabling technologies is presented in the following subsections.

2.2.1 High Intensity VMJ Photovoltaic Cells

One of the enabling technologies of HILPB is the high intensity photovoltaic power receiver, which is used to convert the photonic energy into electric energy. The critical technology of this power receiver is the photovoltaic array that makes up the face of the receiver; it comprises of high intensity Vertical Multi Junction (VMJ) solar cells, which have been developed by scientists at the National Aeronautics and Space Administration

(NASA) John H. Glenn Research Center (GRC) in the early 1990s for use in solar concentrators [35]. The VMJ solar cell technology was acquired in 2011 by MH GoPower

Limited (MHGP), which is based in Taiwan, from Greenfield Solar Corporation. The high- voltage silicon VMJ solar cells have been designed to efficiently operate at sun intensities that exceed 2500 suns of broadband optical energy with a conversion efficiency of up to

25% across all wavelengths in the solar spectrum.

A typical VMJ solar cell is illustrated in Figure 8 and it is made up of an array of integrally bonded miniature silicon vertical junction unit cells, which are connected in series. Depending on the specific application, the number of junctions can be reduced or increased in order to accommodate for the desired overall cell voltage or stack voltage. For example, a typical 40-junction VMJ cell, with a total surface area of 0.78 푐푚2, produces

31.8 Watts at 25.5 Vdc when flash tested with light intensities of 2500 suns; this translates into an electrical power output of 40.4 푊/푐푚2 from an input optical irradiance energy

level of 211 푊/푐푚2 [36]. This is a significant advantage for any application as it can significantly reduce the surface area that is occupied by the solar cells when compared to conventional solar cells that use horizontal junctions and require a large surface area to produce the desired output voltage for the downstream power management and distribution system.

Figure 8: High-Intensity Silicon VMJ Solar Cell (40 junctions, 0.78 푐푚2) [37]

The VMJ cell offers several major advantages due to its unique and rugged design.

First, the need for electrical contacts is eliminated because the cell is illuminated at the side of the junctions, thus increasing the surface area used for photonic energy conversion. In addition, this edge-illumination property eliminates the overall series resistance at high illumination intensities that is usually added during the manufacturing process. The edge- illumination property also improves the cell’s spectral response for short and long wavelengths; the spectral response of the VMJ photovoltaic cell is illustrated in Figure 9.

Figure 9: Spectral Response of a Typical VMJ Solar Cell

The series-connection of the silicon junctions offers one other advantage as it provides a high voltage and low current operation of the VMJ cell, thus adding flexibility towards matching the power requirements for most loads. Furthermore, the need for the typical by-pass protection diodes is also reduced since a very high reversed breakdown voltage immunity is created by the connection configuration of the silicon junctions.

In order to efficiently operate at high intensities, one of the cell properties is the almost linear decrease of internal resistance with increase in intensity. In addition, the structural design of the VMJ cell has been tested and proven to be very robust electrically, mechanically, and thermally. In terms of its thermal properties, the nominal temperature for its optimum efficiency is 25 °C. Increasing the temperature past its nominal point, the cell’s efficiency decreases with increase in temperature; the cells have been proven to

withstand temperatures of up to 600 °C. The performance of a 40-junction VMJ cell has been characterized using the Large Area Pulsed Solar Simulator (LAPSS) at NASA GRC; these current-voltage (I-V) results are illustrated in Figure 10.

Figure 10: VMJ Solar Cell I-V Curves for 100 to 2500 Sun Intensities – Tests Conducted

at NASA GRC’s LAPSS

2.2.2 High Intensity Lasers

The realization of the HILPB technology is possible in part due to the rapid development and availability of high intensity lasers. The laser, which is also known as

“light amplification by stimulated emission of radiation” [38], traces its origins to the early

part of the twentieth century when Albert Einstein developed the foundation which led to the invention of the laser in the late 1950s.

Laser technology has evolved over time as the overall electrical to optical conversion efficiency has improved considerably. One of the latest laser technology is the diode pumped alkali vapor based lasers (DPALs), which can achieve an end-to-end turn- key system electrical efficiency of 25-to-30% [39, 40]. The wavelength of operation for

DPALs is in the near-infrared region.

The DPAL is available in a variety of operational wavelengths, some of which are in the near-infrared region (cesium 895 nm, rubidium 795 nm, and potassium 770 nm), which are ideal for silicon and gallium photovoltaic arrays. For laser power beaming applications, matching the DPAL wavelengths with the photovoltaic cells is necessary in order to achieve optimum end-to-end systems efficiency, i.e. silicon cells at 895 nm

(DPAL’s cesium), and GaAs cells at 795 nm (DPAL’s rubidium) and at 770 nm (DPAL’s potassium) [40].

2.2.3 Directed Energy Systems

The concept of directed energy weapons has been traced by some historians to 212

B.C., when Archimedes may have used mirrors to concentrate the sun light into a laser beam in an attempt to defend the city of Syracuse from an invading Roman fleet. A pictorial illustration is shown in Figure 11 of depicts how the people of Syracuse could have used polished metal to reflect sunlight onto the Roman fleet; the energy was directed accurately by looking through a hole in the polished metal or mirror [41]. There are a few

experiments which have demonstrated this historical claim. Although Arhimedes’ flaming death ray continues to be debated by historians, it is interesting to note that the destructive power of directed energy was recognized almost 22 centuries ago [42].

Figure 11: Arhimedes’ Flaming Death Ray [41]. Artist credit: Grace Smith.

Beaming power to a moving target requires an optical transmitter system that is able to acquire and track the target as well as capable to precisely control and focus the optical beam. A typical optical transmitter system for laser power beaming applications consists of the following subsystems: high energy laser; high power beam shaping optics and control; and target acquisition, tracking and pointing. The optical transmitter system has seen significant improvements in recent years due to the development of directed energy systems developed for military applications that utilize laser weapons. Directed

energy weapons (DEW) have the ability to focus and transmit high-intensity optical energy

(tens of kilowatts) over long distances of hundreds of kilometers. The Hughes Corporation demonstrated the first laser operation in 1960s. Over the past 40-to-50 years, laser systems have seen a tremendous growth as high intensity lasers are used extensively in the manufacturing industry. During the past decade, the laser technology transitioned form chemical lasers to high-power solid-state lasers that are now capable of tens of kilowatts.

With the advancement of optics and laser technology lasers are also being used in military applications. The drive for DEW systems is primary due to the goal of reversing the cost equations. As Major General Jerry D. Harris explained “shooting a $500,000 missile at a

$500 thread is not cost-effective” [43]. A historic perspective of successful research and development in the area of DEW systems in support of the United State Air Force is illustrated in Figure 12.

Figure 12: History of Research and Development in Directed Energy Weapons [43]

Directed energy weapons systems have been developed since the 1960s by the U.S.

Government along with a number of Defense contractors including: Boeing, Northrop

Grumman, Lockheed Martin, L-3 Communications, and others. Northrop Grumman has also made significant improvements in the area of solid-state high-power laser systems.

Under funding form the U.S. Defense Department for the Joint High Power Solid State

Laser (JHPSSL) program, Northrop Grumman has developed the most powerful continuous-wave solid state laser. The laser system has been demonstrated to generate more than 100 kW of continuous, highly concentrated, light beam, which was operated for more than five minutes; the electro-optical efficiency was 19.3 percent. The JHPSSL laser system is based on “laser amplifier chains” where each chain produces 15 kW of power.

The modularity of the system allows the customer to use these building blocks to build a system based on the desired laser power requirements [44, 45, 46].

Figure 13: Potential Applications for the Joint High Power Solid-State Laser [46]. Artist

concept, courtesy of Northrop Grumman.

One of the most recent and successful application of DEW is the Airborne Laser

(ABL) research and development program, whose concept of detecting and destroying

ballistic missiles has been developed since the late 1980’s, and has been part of the U.S.

Ballistic Missile Defense System since 1996. The ABL weapons platform is a modified

Boeing-747 and currently it is capable of detecting and destroying targets as far away as

600 km. In 2014, Boeing has developed the High Energy Laser Mobile Demonstrator (see

Figure 14), which consists of a 10 kW laser that can be mounted on mobile platforms such as vehicles and ships. The system was successfully demonstrated using an Oshkosh military vehicle by detecting, tracking, and destroying aerial targets such as 60 mm mortars

(measuring 10 inches in length) and rockets traveling at 600-to-1000 miles per hour. These tests were successfully demonstrated in maritime conditions such as wind, rain, and fog

[47]. The demonstrated capability to focus the laser beam onto a specific target, lock onto the target in seconds, and track the target while it is moving at very high speeds makes this turn-key solution very appealing to various branches of the U.S. military. The success and maturity of the DEW technology is directly applicable to HILPB [48]. More recently,

Lockheed Martin has completed the development of a similar system but higher power; the successful demonstration of the 60 kW-class laser system for the US Army is now a work record [49].

Figure 14: High-Energy Laser Mobile Demonstrators by Lockheed Martin (left) [49] and

Boeing (right) [50]; © Lockheed Martin (left image), © Boeing (right image)

2.2.4 HILPB Power Receiver

The HILPB power receiver is a key subsystem within the HILPB technology as it is the target of the focused laser energy, and it is used to convert the laser’s optical energy into electrical energy. Since the HLIPB technology is able to focus large amounts of energy into a small target area, the power receiver must be able to dissipate the excess heat that results from the unconverted photonic energy. The HILPB power receiver consists of high intensity VMJ solar cells that are mounted on top of a heat sink, which is capable of dissipating the large amounts of heat from unconverted photonic energy.

The design and construction of the HILPB powered receiver by the ISSL team is detailed in [3, 4, 7, and 8]. A top-level summary of the process used to mount the VMJ

solar cells to the heat sink is illustrated in Figure 15-a). Figure 15 also shows a number of air-cooled and water-cooled HILPB receivers, which were built to optimize the photonic energy conversion efficiency.

a) HILPB Receiver Build-Up b) Air-cooled HILPB Receiver

c) Water-cooled HILPB Receiver d) Air-cooled HILPB Receiver

Figure 15: Air-Cooled and Water-Cooled HILPB Power Receivers Built by the ISSL

Team [3-8]

2.3 HILPB: Author’s Contribution and Technology Status

During the five-year tenure of the HILPB program, various testing campaigns were designed and performed in order to advance the technology. One of the first test programs at the ISSL aimed at determining the feasibility of the technology by testing the VMJ cell with a high-power laser to determine whether the VMJ solar cell could withstand high- intensity optical energy; these technology feasibility tests were performed at Northrop

Grumman’s laser facility. Following the successful feasibility demonstration of the HILPB technology, other research and development testing campaigns followed to further advanced the HILPB technology.

2.3.1 HILPB Experimental Results – Optimal Operating Laser Wavelength

In an effort to improve the conversion efficiency of the HILPB system at high intensities, one of the major test programs at the ISSL was to determine the optimal operating wavelength of the laser system with the VMJ cell. In order to test the VMJ cell with a number of high power continuous wave semiconductor lasers, the ISSL team (which included the author of this dissertation) traveled to Lissotschenko Mikrooptik GmbH

(LIMO) Laser test facility in Dortmund, Germany. A total of three high power continuous wave laser systems were selected for these tests with operational frequencies near the theoretical band-gap of the photovoltaic VMJ cells: 808 nm (LIMO70-F200-DL808), 940 nm (LIMO70-F200-DL940), and 976 nm (LIMO70-F200-DL976). Figure 16 shows one of the laser systems used during testing. It must be noted that these commercial LIMO lasers systems are turn-key solutions; the diode laser module in Figure 16-b) and the optical

fiber cable in in Figure 16-c) are part of the complete system shown in included in Figure

16-a).

a) LIMO Laser System b) Diode Laser Module c) Optical Cable

Figure 16: LIMO 350 Watts Solid-State Fiber-Coupled Diode Laser System

The experimental set-up consisted of a single cell HILPB receiver, a three-axis positioning system for the power receiver, cooling fan, data collection electronics, and a personal computer – an illustrative image of the experimental set-up is shown in Figure 17.

Figure 17: Hardware Set-up for the Frequency Optimization Tests with Beam

Homogenization Optics at Limo’s Laser Facility in Dortmund, Germany

The experimental results from testing a single VMJ cell with the three LIMO laser systems are shown in Table II, Table III, and Table IV.

TABLE II: TEST RESULTS USING THE 808 NM WAVELENGTH LASER SYSTEM [5] LIMO70-F200-DL808 LIMO70-F200-DL808 Rated Operating Adj. Optical Impinging VMJ Current Optical Optical Window Optical Peak Conversion Receiver Setpoint Power Power Transmittance Power Power Efficiency Temp. Amps (A) Watts (W) Watts (W) Watts (W) Watts (W) Watts (W) (%) (°C) 10 1.7 1.581 1.478235 0.6282 0.3131 49.83 22.5 20 20.3 18.879 17.651865 7.5020 1.8050 24.06 28.7 30 38.9 36.177 33.825495 14.3758 3.0695 21.35 35.4 40 56.4 52.452 49.04262 20.8431 3.9837 19.11 41.8 49.4 70 65.1 60.8685 25.8691 4.6798 18.09 47.2

8 7 6 5 4 3 2 1

0 Peak Electrical Output PeakElectrical Output (W) 0 5 10 15 20 25 30 Continuous Optical Input (W) 31

TABLE III: TEST RESULTS USING THE 940 NM WAVELENGTH LASER SYSTEM [5] LIMO70-F200-DL940 LIMO70-F200-DL940 Rated Operating Adj. Optical Impinging VMJ Current Optical Optical Window Optical Peak Conversion Receiver Setpoint Power Power Transmittance Power Power Efficiency Temp. Amps (A) Watts (W) Watts (W) Watts (W) Watts (W) Watts (W) (%) (°C) 10 9.9 9.207 8.608545 3.6586 1.5198 41.54 24.4 20 25.7 23.901 22.347435 9.4977 3.5398 37.27 25 30 40.9 38.037 35.564595 15.1150 5.0675 33.53 27.6 40 55.1 51.243 47.912205 20.3627 6.1611 30.26 30.1 50.8 70 65.1 60.8685 25.8691 6.8263 26.39 32

TABLE IV: TEST RESULTS USING THE 976 NM WAVELENGTH LASER SYSTEM [5] LIMO70-F200-DL976 LIMO70-F200-DL976 Rated Operating Adj. Optical Impinging VMJ Current Optical Optical Window Optical Peak Conversion Receiver Setpoint Power Power Transmittance Power Power Efficiency Temp. Amps (A) Watts (W) Watts (W) Watts (W) Watts (W) Watts (W) (%) (°C) 10 9.8 9.114 8.52159 3.6217 1.5481 42.74 24.1 20 25.4 23.622 22.08657 9.3868 3.5402 37.71 24.7 30 40.9 38.037 35.564595 15.1150 5.1722 34.22 27.5 40 56 52.08 48.6948 20.6953 6.4459 31.15 30.1 50 70 65.1 60.8685 25.8691 7.2430 28.00 32.6

The output power characteristics of each wavelength laser system were also measured; the maximum I-V power points are illustrated in Figure 18. It must be noted that the three laser beams are invisible to the human eye as their wavelengths are in the near infra-red region. The coloring effect of the laser beam (green for 976 nm, yellow for

940 nm, and purple for the 808 nm) is due to the aliasing effect produced by digital camera.

Figure 18: Maximum Output Power for Each Wavelength Laser System [5]

The experimental results from testing the photovoltaic VMJ cell using three high power continuous-wave laser systems with operational frequencies of 808 nm (LIMO70-

F200-DL808), 940 nm (LIMO70-F200-DL940), and 976 nm (LIMO70-F200-DL976) demonstrated that the 976 nm wavelength produced the optimal performance, i.e. maximum electrical energy as a function of the input optical intensity and higher optical- to-electrical energy conversion efficiency as depicted in Figure 19 and Figure 20, respectively. Additional information and analysis is available in [5].

Figure 19: Conversion Efficiencies for all Wavelengths Laser Systems [5]

Figure 20: Optical Input vs Electrical Output for All Wavelength Laser Systems [5]

2.3.2 High Power Laser Laboratory at CSU’s ISSL

The HILPB research and development program at the ISSL was an on-going four- year effort. During this time, the technology evolved and matured at a fast pace as the demonstrated power density per unit area made ISSL the world leader in the field of wireless power transfer. A High Power Laser Laboratory was constructed at ISSL in order further research and develop the HILPB technology. The laboratory shown in Figure 21

and Figure 22, consisted of a 350 W continues-wave diode laser system manufactured by

Limo; the ISSL team traveled to the Limo laser facility in Dortmund, Germany, where it evaluated the optimal wavelength of a number of laser systems and purchased the turn-key laser system depicted in Figure 16. The laser facility also included a 4’x10’ optical bench, custom gimbal system for the HILPB receivers as shown in Figure 15-c), custom PMAD systems, and multi-channel data acquisition electronics. Some of the tests performed at the ISSL, which are detailed in [3-8] include: determination of the appropriate geometry for the HILPB power receivers when subjected to a laser beam that has a Gaussian energy profile, beam profile characterization, parallel cell back-feeding, beam homogenization optics, peak power density, and optimal VMJ cell thickness.

Figure 21: ISSL’s High-Power Laser Laboratory at CSU (Front View)

Figure 22: ISSL’s High-Power Laser Laboratory at CSU (Laser System View)

2.3.3 Current Status of the HILPB Technology

To advance the HILPB technology, the ISSL team conducted HILPB experiments at Northrop Grumman Space Technology’s high-power laser laboratory, at Limo’s laser facility in Dortmund Germany, and at the ISSL’s High Power Laser Lab. The experimental demonstrations conducted at the ISSL’s High Power Laser Lab, utilized a high intensity

DPAL-based laser operating at a wavelength of 980 nm. The current status of the HILPB technology is summarized below via three experimental demonstrations.

First, an experimental demonstration was designed to determine the peak power density of a single 40-junction VMJ cell. To this end, a single VMJ cell was mounted onto a HILPB power receiver with an active water thermal management system. The laser beam was placed in proximity of the VMJ cell. Forced air was also induced across the face of the VMJ cell to achieve maximum thermal transfer on top and bottom of the VMJ cell; this thermal management system maintained the receiver temperature at approximately 4-to-8

ºC. The experimental set-up and the I-V characteristics are illustrated in Figure 23. The experimental results of a single VMJ cell yielded an output peak power density of

19.6 푊/푐푚2 from an input optical power density of 67.5 푊/푐푚2 with a net conversion efficiency of 24 %.

Second and third, other experiments were designed to address the challenge of the

Gaussian beam profile [7, 8]. To this end, a 9-cell parallel array HILPB receiver was constructed and tested under two experimental set-ups: one experiment was executed with the natural Gaussian laser beam profile and another experiment that utilized flat-top optics used to homogenize the laser beam. Figure 24 illustrates the experimental set-up consisting of the same 9-cell parallel array HILPB receiver being illuminated with the natural

Gaussian profile of the laser beam. In this case, the HILPB receiver produced an electrical power output of 38 W with a net conversion efficiency of 38 %. Figure 25 illustrates the experimental set-up that utilized flat-top optics to force a square beam onto the HILPB receiver. The square illumination of the HILPB receiver provided a uniform illumination of the VMJ cells and yielded 45 W of electrical power with a net conversion efficiency of

41 %. In conclusion, it was demonstrated that the uniform distribution of the laser beam,

created by the beam shaping optics, improves the overall conversion efficiency of the

HILPB power receivers by 10 %.

To summarize the experimental results, Table V details the power efficiency numbers for the HILB tests with a single VMJ cell, a 9-cell HILPB power receiver with the beam shaping optics, and a 9-cell HILPB power receiver without the beam shaping optics.

TABLE V: SUMMARY OF HILPB TEST RESULTS – PEAK POWER DENSITY 1-Cell HILPB Receiver 9-Cell HILPB Receiver 9-Cell HILPB Receiver Gaussian Laser Beam Gaussian Laser Beam Uniform Laser Beam Illuminated Surface Cell-Area (푐푚2) 0.65 5.85 5.85 Gross Input Power with Overfill (W) 135 368.5 368.5 Net Input Power on Cell (푊/푐푚2) 67.5 17.2 19.1 Net Conversion Efficiency (%) 24% 38% 41% Output Power Density (푊/푐푚2) 19.6 6.58 7.62

Figure 23: Peak Power Density Experiment – Single VMJ Cell with Gaussian Laser

Beam (Water and Air Cooling)

Figure 24: Peak Power Density Experiment – HILPB 9-Cell Parallel Array Receiver with

Gaussian Laser Beam (Air Cooling)

Figure 25: Peak Power Density Experiment – HILPB 9-Cell Parallel Array Receiver with

Uniformed Laser Beam (Flat-Top Optics and Water Cooling)

CHAPTER III

ULTRAFAST ENERGY CAPTURE & HIGH ENERGY DENSITY SYSTEM

Chapter 2 has demonstrated that the HILPB technology is ready to be used in power beaming applications. The goal of the AFRL program detailed in this dissertation was to beam power to a MUAV in order to re-charge the on-board Li-ion batteries. Tracking an in-flight MUAV with a high intensity laser for extended periods of time (tens of minutes) in order to charge the on-board Li-Poly battery is not practical. This chapter details a novel energy storage solution for the MUAV application via the development of a high energy density system that is also capable of capturing and storing intermittent high energy pulses of short duration or pulsed energy. The novel energy storage system will be able to absorb, transfer, and store large amounts of electrical energy at extremely fast rates, i.e. tens of seconds, while still maintaining a high energy density, within the weight and size constraints of the MUAV.

Therefore, the goal is to design and develop an energy storage system that will meet the MUAV’s energy storage requirements and enable the HILPB technology to beam power to the MUAV while eliminating the practical limitation to continuously track the

MUAV for tens of minutes to charge the on-board battery pack. The next section presents a thorough literature review of currently available options in energy storage.

3.1 Electrical Energy Storage

Energy use and storage on a major scale has become a necessity for the modern technological society, as a wide range of small and large systems are employed to meet these demands [51]. Electrical energy storage technologies are usually classified as either electrical or thermal [52]. All systems and technologies, whose external interface is electrical, fall under the category of electrical energy storage. Utilizing a variety of techniques, electrical energy can be stored directly or indirectly: mechanically (rotating flywheels, compressing air, pumping water), thermally (hot water), chemically (batteries, flow cells, fuel cells and other hydrogen-based systems), and electrically and magnetically

(capacitors, superconducting coils, and magnets) [53, 54, 55, 56, 57, 58]. Figure 26 depicts a pictorial illustration of the various types of electrical energy storage system and technologies.

Figure 26: Electrical Energy Storage Systems and Technologies. Adapted from [54].

All electrical energy storage systems are characterized by two fundamental parameters: energy density and power density. Energy density is defined as the amount of energy that can be stored within a given volume or weight. The second parameter, power density, is the rate at which the energy is transferred into or out of the storage system. The higher the power density, the less time it takes for a device to absorb or deliver energy.

Therefore, the ideal energy storage system would have a high energy density and also a high power density [59].

However, there is a discrepancy between these energy storage technologies as some have high energy storage capabilities but lack the power density, while others have high power density but are deficient in their energy density. In terms of portable electrical energy storage systems, the Ragone plot shown in Figure 27 depicts the specific power and energy densities of various energy storage devices along with the respective charge/discharge time durations. Combustion engines offer the best of both worlds (high

energy and power density); batteries and fuel cells have the highest energy storage potential, while capacitors are at the opposite end of the spectrum with high power densities.

Figure 27: Ragone Plot of Various Electrical Energy Storage Technologies with Charge

Time Durations. Adapted from [60] and modified. Used with permission, Appendix D.

Fuel cells have superior capabilities in terms of energy density per unit of weight when compared to the other energy storage technologies that are illustrated in Figure 27.

Although discovered during the mid-nineteenth century and currently used in a variety of applications, the fuel cell technology is still under continued research and development.

Due to expensive materials and low volume production, the cost is still relatively high, thus limiting the realm of its applications. The slow turn-on response along with cost, size, and

weight constraints prevents this technology to being used as the energy storage system on board the MUAV. The mini fuel cell technology however, which is not yet available but currently under development, aims at competing and possibly replacing batteries for numerous applications such as notebook computers, mobile phones, and other [61, 62].

Flywheel energy storage (FES) and superconducting magnetic energy storage

(SMES) systems offer alternative means of storing electric energy. An SMES unit uses a large superconductive coil at cryogenic temperatures in order to store energy in its magnetic field – the power density and energy density of SMES units are depicted in Figure

27 [63]. The FES technology uses the moment of inertia of the flywheel to store energy mechanically in the form of kinetic energy (see Figure 28). Depending on its design an

FES system can store more energy than a SMES unit can, as illustrated in Table VI.

Although both technologies are very efficient, the system complexity, size, weight, and required maintenance do not make them viable solutions for low power output applications such as MUAV applications [57, 64, 65, and 66].

Figure 28: Flywheel Energy Storage System

A summary comparison of the fundamental characteristics for the energy storage technologies illustrated in Figure 27 are detailed in Table VI. For the MUAV application discussed in this dissertation, the primary requirement is to use an energy storage technology that can absorb intermittent high energy pulses at extremely fast rates. Figure

29 depicts the re-charge duration of batteries, flywheels, and ultracapacitors. Flywheels cannot be used for the MUAV application due to cost and size constraints. Batteries and ultracapacitors, however, are evolving technologies with contrasting characteristics that could be used on-board the MUAV; these two technologies are discussed in the Section

3.1.1 and Section 3.1.2, respectively.

TABLE VI: COMPARISON OF ELECTRICAL ENERGY STORAGE TECHNOLOGIES [67, 68, 69]

Figure 29: Comparison of Recharge Time Duration for Various Electrical Energy

Storage Technologies. Courtesy of Schneider Electric [70]. Used with permission,

Appendix D.

3.1.1 Battery Energy Storage

Alessandro Volta’s discovery of “voltaic electricity” in 1800 led to the invention of the first battery, which was constructed using copper and zinc discs separated by a layer of cloth soaked in brine, also known as the Voltaic Pile. Several improvements were made to the Voltaic Pile during the 1800s and early 1900s. Towards the end of the nineteenth century, batteries have emerged as a means of storing energy and now are known as one of the most cost-effective energy storage technologies available on the market today. Inside

the battery, self-contained unit cells connected in series and parallel, are used to store the energy chemically. During discharge, batteries undergo internal chemical reactions that convert the stored chemical energy into electrical energy; the same electrochemical reactions also occur during the charging phase [52, 53, 61]. The basic elements of a battery along with the electron flow during the charging and discharging phases are illustrated in

Figure 30.

Figure 30: Battery – Basic Elements and Operation. Reprinted from [61]. Used with

There are three main categories of battery technologies: primary batteries, which are discarded after one discharge; secondary batteries that can be re-charged; and specialty batteries, which are specially designed for military and medical applications. Some of the secondary battery technologies include lead-acid, Lithium (Li) ion, nickel-cadium (Ni-Cd),

nickel-zinc (Ni-Zn), and various rechargeable alkaline batteries [61]. The energy storage capabilities of various rechargeable battery technologies are illustrated in Figure 31.

Figure 31: Rechargeable Battery Systems – Energy Storage Capabilities. Reprinted from

[61]. Used with permission, Appendix D.

As illustrated in Figure 31, Li-ion batteries offer the most energy storage capability of common re-chargeable battery technologies. The emergence of fully electric vehicles has led to a demand increase for Li-ion batteries; for example, Tesla Motors® is in the process of building its own battery production facility, the Tesla Gigafactory®, which will be fully operational by 2018. In response to the increased demand for lithium-ion batteries, new research in this field has led to the development of a number of start-up battery companies such as A123Systems LLC, Sakti Inc., and others which are improving the state-of-the-art in battery technology. Sakti Inc. is re-designing the current topology of Li- ion batteries using 100% solid state materials, thus aiming to eliminate the liquid ion material.

Figure 32: Li-ion Battery – Basic Elements and Operation. Reprinted from [71]. Used

with permission, Appendix D.

The Li-ion battery cells manufactured by A123Systems LLC can be fully re- charged in 60 minutes using the recommended standard charge method or in 12 minutes using the fast charge method to 80% state of charge (SOC) [72]. It must be noted, however, that Li-ion batteries are charged using constant current for 80% of their capacity, and constant voltage for the remaining capacity needed to reach 100% SOC, which takes considerably more time. Although the Li-ion batteries manufactured by A123Systems Inc. represent a viable solution for the energy storage system currently used on board the

MUAV, the time duration to charge the batteries to 80% of their capacity still requires tens of minutes. Therefore, an alternative energy storage technology is required to capture

intermittent high intensity pulsed energy. An emerging energy storage technology, which is an alternative to Li-ion batteries, is the ultracapacitor.

3.1.2 Ultracapacitor Energy Storage

The phenomenon of storing electrical charge on different surfaces dates back to ancient times, as it was originally discovered through the rubbing of amber (the triboelectric effect); as a side note, the Greek word for amber is also at the origin of the word “electricity” [51]. However, it was only in the mid-eighteenth century that this phenomenon was understood as in 1745, the first form of a capacitor was invented by Pieter van Musschenbroek while working at the University of Leyden. Using two electrodes, one on the inside and one on the outside of a jar, he created a device that stored static electricity, which later became known as the Leyden jar (see Figure 33); this was a significant discovery as the earliest unit of capacitance was actually the “jar”. It must be noted that during that period of time, the same device was also independently discovered by Ewald

Georg von Kleist, a German inventor [73].

Figure 33: Discovery of the Leyden jar in 1746

The capacitor has evolved over the years, and its basic construction now consists of two metal plates or conductors, that are separated by a non-conductive substance also known as a dielectric. The electric field generated within the dielectric material is used to store the energy. Based on the dielectric medium that sustains the electric field between the two conductors, capacitors are divided into two categories: electrostatic and electrolytic

(see Figure 34). The electrochemical double-layer capacitors (EDLC), which are a special class of electrolytic capacitors, do not use the conventional dielectric material to store the charge. Instead, two layers of the same substrate are implemented in order to store the charge on a much larger surface area and thus achieve extremely high capacitance values.

As a result of this technology, the EDLC which is also known as supercapacitor or

ultracapacitor, can achieve much higher energy densities than regular capacitors while still maintaining the conventional capacitor properties of charge separation or power density

[74].

Figure 34: Classification of Capacitor Technologies. Adapted from Wikimedia

Commons

The development of the ultracapacitor began in 1957 when the classical capacitor was completely transformed when the patent for the first electrochemical capacitor was filed by Becker, an engineer at General Electric [75]. Initially not much attention was given to this technology until 1966 and 1970 when the Standard Oil Corporation in

Cleveland, Ohio (SOHIO) used it in combination with other chemical compounds and

began marketing it as a high capacitance energy storage device [76, 77]. The ultracapacitor is a relatively new technology since only in the nineties it has found its use in EVs.

Furthermore, in 1989 a development program sponsored by the DOE has put the ultracapacitor on the industry map by setting short term and long term goals for the time frame of 1998-to-2003. Figure 35 illustrates the evolution of the EDLC technology.

a) US Patent 2800616 (1957) [75] b) Modern ultracapacitor (2016) [78]

Figure 35: Evolution of the Ultracapacitor Technology. Adapted with permission,

Appendix D.

Capacitors and batteries are the most commonly used electrical energy storage devices. The method in which they store energy, however, sets them apart at opposite ends of the spectrum when it comes to power density and energy density. Ultracapacitors make use of the electrostatic effect, where energy is stored based on the movement of ions at the layer between the electrode and the electrolyte. By storing the charge physically, there are

no major changes or chemical reactions in the structure of the material that holds the charge, allowing the ultracapacitor to have a high power density (the charge and discharge time is on the order of seconds or milliseconds), and an extremely high cycle life (500,000

– 1,000,000 cycles). The battery, on the other hand, stores energy in chemical form where a physical change occurs between the discharged state and the charged state. Thus, the battery can store much more energy than an ultracapacitor, but its discharge rate is on the order of minutes to tens of minutes, while its charge rate is even higher. Moreover, the cycle life of a battery is much shorter than that of an ultracapacitor (300 – 5,000 cycles)

[79, 80]. A summary of these characteristics are detailed in Table VII. Some of the ultracapacitor manufacturers include: Maxwell Technologies, New Energy Storage System

Capacitor (NESSCAP), Capp-XX, and Panasonic, LSMtron, Ioxus, Illinois Capacitor,

AVX, and others.

TABLE VII: COMPARISON OF THE STATE-OF-THE-ART LITHIUM-ION BATTERIES AND ULTRACAPACITORS [81, 82, 83] State of the Art Characteristic Ultracapacitor Lithium-Ion Battery Charge Time Duration 10-60 minutes 1-30 seconds Cycle Life <5,000 @ 1C rate 1 million Energy Density (Wh/kg) 10-200 5 Power Density (W/kg) 1,000-3,000 Up to 10,000 Cycle efficiency (%) <70% to >90% <90% to >95% Cost per Watt-hour (Wh) $0.5-$2 / Wh $10-$20 / Wh Cost per kW $75-150 / kW $25-$50 / kW Cell voltage range 2.3 to 3.0 Vdc 3.6 to 4.2 Vdc Service life 5 to 10 years 10 to 15 years Charge temperature 0 to 45°C –40 to 65°C Discharge temperature –20 to 60°C –40 to 65°C

3.2 Problem Definition, Objective, and Scope

Li-ion batteries are used as the current energy storage system used on board the

MUAV. The manufacturer recommended re-charge time for the batteries used on-board the MUAV is approximately one hour. The re-charge time may be reduced if these batteries are replaced with the Li-ion technology offered by A123systems Inc [72], as these batteries could be recharged at a faster rate. The Li-ion technology is ever evolving as the new state-of-the art Li-ion batteries may further reduce the re-charge time. However, for the specific application addressed in this dissertation, the goal is to use the HILPB technology to re-fuel the MUAV in the shortest time possible. Since HILPB can deliver large amounts of energy, the ideal and desired scenario is to implement an energy storage system on-board the MUAV that is able to capture the beamed energy in tens of seconds rather than tens of minutes, so that the time used to track the MUAV with a high intensity laser is minimized.

3.2.1 The Solution: Hybrid Energy Storage System

Batteries and ultracapacitors are energy storage technologies that are at the opposite end of the spectrum in terms of power and energy density per unit of weight, as it was illustrated by Figure 27 and Table VII. These energy storage technologies have contrasting but complimentary characteristics, as batteries have high energy density while ultracapacitors have high power density. Therefore, the novel concept brought forth by this dissertation is that of using the ultracapacitor and the battery in a hybrid configuration, where the ultracapacitor is utilized at the input of the system, rather than at the load side as

it is used in typical applications, in order to absorb the large amounts of transient intermittent pulsed energy. Once the energy is stored, the ultracapacitor bank transfers the stored energy to the battery bank through a controlled discharge rate, by trickle-charging the Li-ion batteries. The block diagram of this energy storage system is illustrated in Figure

37, denoted as the ultrafast capture and high electric energy density storage system. A representative block diagram of how the proposed hybrid energy storage system may be implemented on-board the MUAV is shown in Figure 37.

Hence, the objective of this dissertation is to investigate the feasibility of the ultrafast capture and high electric energy density storage system, which is to emulate a yet non-existing super-device, by controlling the power transfer between the two technologies, and thus creating an energy storage system that has a high energy density and a high power density, as illustrated in Figure 36.

Figure 36: Proposed Ultrafast Capture and High Electric Energy Density Storage System.

Adapted from [84] and modified (Courtesy of Electronic Design).

Figure 37: Block Diagram of Proposed Ultrafast Energy Capture and High Electric

Energy Density Storage System

3.3 Literature Review

A comprehensive literature review of ultracapacitor applications and related hybrid configurations of ultracapacitors and batteries for various energy storage systems was performed. A hybrid electric propulsion system for UAVs using batteries and combustion engine was successfully built in [85]. Electric aircrafts may also be powered by hybrid energy storage systems of fuel cells and ultracapacitors [86]. Although the characteristics of the ultracapacitor and the battery are fundamentally different, they complement each other. For this reason, there are numerous applications where the battery and ultracapacitor are used in a hybrid configuration in order to facilitate various applications and technologies as detailed in [54, 87]. The hybridization of ultracapacitors along with batteries is driven by the specific application requirements as both energy storage devices are used in tandem in order to compensate for each other’s shortcomings. The use of the ultracapacitor technology as stand-alone units or in a hybrid configuration energy storage

system is encompassed by two major industries: the transportation industry and the power grid industry. Furthermore, the top 5 markets for ultracapacitors and hybrid ultracapacitor- based energy storage systems are as follows: hybrid buses, renewable energy, power grid, automotive, and railway [88].

Figure 38: Top 5 Markets for Ultracapacitors-Based Energy Storage Systems [88].

Courtesy of Maxwell Technologies, Inc. Used with permission, Appendix D.

3.3.1 Hybrid Battery-Ultracapacitor ESS in the Transportation Industry

Ultracapacitors and hybrid energy storage systems of ultracapacitors along with a primary energy storage source (batteries, fuel cells, combusting engine) are widely used in the transportation industry, where the primary markets that use these energy storage solutions include: automotive (electric vehicles and charging stations), buses (mass transit), rail (trains and trams), trucks (heavy transportation vehicles), aircraft, and industrial machinery (forklifts and cranes). Each market was researched and investigated to determine the use of ultracapacitors and batteries hybrid energy storage systems.

Energy Recuperation with Peak Power Assistance

In the transportation industry regenerative power systems are found in electric vehicles with applications such as regenerative braking with acceleration assistance.

Heavy industrial machineries such as forklifts and cranes employ energy recuperation systems to store regenerative energy directly in ultracapacitors. When lifting or hoisting operations are initiated, a sudden burst of power is required; the ultracapacitors are used to deliver the stored regenerative energy to the load.

Regenerative braking systems are deployed in hybrid-electric vehicles and all- electric vehicles to harvest the kinetic energy from braking systems. The duration of a braking event varies from seconds to a few minutes. Due to the high frequency and low time duration of these events coupled with bursts of very high-power energy generation, ultracapacitors are a good fit for this application due to their characteristic high power density. In these applications, the energy is injected and stored in ultracapacitors only.

The energy stored in ultracapacitors is not transferred to the battery system, but it is rather delivered directly to the drive-train via a DC-to-DC converter to satisfy the peak power demands during acceleration events [89].

In conclusion, for energy recuperation applications, the ultracapacitor is primarily used as a stand-alone energy storage element to store the regenerative energy until is required by the load; unlike the application discussed in this dissertation, where energy captured by the ultracapacitor is transferred to the primary battery by trickle-charging the battery. In other words, the ultracapacitor will not drive the MUAV electrical loads directly.

Figure 39: Pictorial Depiction of Ultracapacitors in Regenerative Braking Systems [90].

Courtesy of Maxwell Technologies, Inc. Used with permission, Appendix D.

Engine Start Assist

There is a growing demand in the transportation industry to start truck engines using ultracapacitors instead of batteries alone. This demand is driven by the challenges associated with the traditional battery packs such as limited start duty-cycles, long charge times, and weight. The new generation of heavy-duty trucks incorporate additional amenities for drivers such as refrigerator, microwave oven, television, global positioning system (GPS), and others personal electronic devices. Each of these amenities, however, increase the truck’s power demands and create additional strain on the battery pack due to

the additional power loads. Also, extreme cold and hot weather temperatures negatively impact the battery reliability. Most importantly, trucks are left idling for long periods of time to avoid the risk of engine not starting, which leads to unnecessary fuel consumption and pollution. The solution implemented by truck manufacturers is a hybrid combination of ultracapacitors and batteries, where the ultracapacitor is used on the load side to provide the engine-crank burst of energy required to start the engine, as illustrated in Figure 41

[91].

Figure 40: Pictorial Depiction of Hybrid Ultracapacitors and Batteries in Engine Start

Systems [91]. Courtesy of Maxwell Technologies, Inc. Used with permission, Appendix

Other Transportation Applications: Rail, Aircraft, Cranes, and Charging Stations

Similar to the electric vehicles, the rail industry uses the ultracapacitor technology for locomotive engine start applications and to recuperate braking energy which is then used in the propulsion system. In addition, ultracapacitors are also used as energy buffers or voltage stabilization devices to bridge the power gap and stabilize the power grid by avoiding overloading the power grid when multiple electric trains are operational at the same time.

Aircrafts make use of ultracapacitor to open aircraft doors in the event of power failures. The ultracapacitor technology is used due to its reliability and ability to operate in harsh environments. In these applications, the ultracapacitor is used to store

“emergency” electric energy and deliver it when the system is activated.

Forklifts and cranes represent another major market of ultracapacitor applications, where they are used in conjunction with a primary energy source. Fuel cells are replacing traditional lead-acid batteries as primary energy sources because the batteries’ performance decreases with use, time, and variation in temperature. Ultracapacitors are used in hybrid configuration with fuel cells to recover the braking/dropping energy, which is then used in peak power mode during lifting operations.

With the recent demand of electric vehicles, electrical energy charging stations are being built to meet this demand. The ultracapacitors are used as peak energy storage devices to meet the demand in peak power when multiple electric vehicles are charged simultaneously and thus reduce the stress on the power grid. Hence, in this type of application, the ultracapacitor is used as the primary energy storage element, within the

charging station and on the load side, to supply the peak power demand, from the charging station to the electric vehicles [69].

Figure 41: Pictorial Depiction of Proposed Charging Station for Electric Vehicles [69].

3.3.2 Hybrid Battery-Ultracapacitor ESS in the Power Grid Industry

The power grid plays a major role in the world we know today as it is used to generate, transmit, and distribute electrical power. As illustrated in Figure 42, the power grid is an interconnected network of electrical power systems, which are used to deliver electricity from suppliers to consumers. This is a highly complex network as it spans wide geographical regions and manages wide voltage ranges of 100 V to 1 MV, while ensuring that the electrical energy is delivered reliably and securely. The electrical grid is becoming more complex due to the increase in additional electrical loads from the electrification of the transportation industry and due to the increase in distributed power generation plants that include various renewable energy sources such as solar and wind [92].

Figure 42: Pictorial Depiction of the Electrical Power Grid. Adapted from [93].

Ultracapacitor Applications in Power Generation, Transmission, and Distribution

The ultracapacitor technology is implemented extensively in the power grid industry as hybrid energy storage systems that are used in power generation, transmission, and distribution with applications that include capacity firming/ramping of renewable

energy sources, peak power shaving and load leveling, wind pitch control, frequency regulation, voltage control and power quality, and spinning reserve.

The environmental concerns of increased pollution from generating power using fossil fuels, have driven the demand for renewable energy sources and distributed energy generation plants. However, power generation from wind and solar is intermittent in nature due to variations in wind speed or could coverage, respectively. Capacity firming of renewable energy sources is accomplished through the use of ultracapacitors as an energy buffer on the load side, to firm the power output and thus ride-through these intermittent events [94].

Hybrid battery/ultracapacitor ESS are also used in DC microgrid applications [95].

Other similar applications, where ultracapacitors are used as energy buffers on the load side include peak power shaving and load leveling due to peak power consumption spikes caused by variable loads, where ultracapacitors are used to supply the peak power demand.

Voltage control and power quality is another example where ultracapacitors are used to avoid a temporary voltage sag due to fast and high energy load demands until a secondary energy source becomes active. A similar application is the uninterruptable power supply

(UPS), where ultracapacitors are used as energy buffers on the load side to provide energy during power failures and during the start of back-up power systems such as fossil fuel generators. Furthermore, spinning reserve applications use ultracapacitors to replace

“peaker” fossil-fuel power plants, which operate continuously in idle mode in case of a power transmission outage or failure. By eliminating the continuously run “power peakers” with ultracapacitors, increases the power plant’s efficiency and reduces cost by eliminating unnecessary consumption of fossil fuel.

Frequency regulation in the grid power generation is necessary to compensate for over-generation and under-generation of electricity; these power fluctuations are balanced by rapid charging and discharging of ultracapacitors. In wind pitch control applications, ultracapacitors are incorporated into the design of wind turbines to serve as back-up power or peak power to orient the rotor blades for to maximize the wind energy or in a fail-safe position if there is a power loss condition [92].

In essence, the use of ultracapacitors and hybrid ultracapacitor-based energy storage systems is rising in power grid applications in order to mitigate instability concerns cussed by the increase in renewable energy sources and distributed power generation plants. Hence, a smart power gird is being developed using the concept of “thinking” energy and “acting” power to deal with short-term high-power transient electrical loads

[88].

3.3.3 Ultracapacitor Applications

As detailed in Section 3.3.1 and Section 3.3.2, hybrid battery-ultracapacitor ESSs are used extensively in the transportation industry and the power grid industry.

Ultracapacitors are also used in other industries such as consumer electronics, military, aerospace, industrial, renewables, and others – a complete list along of industries with the applicable ultracapacitor application is depicted in Table VIII.

The medical industry represents another market domain for ultracapacitors. For example, ultracapacitors are used in uninterruptible power supplies (UPS) to provide back- up power. Peak power applications in medical equipment represent another market for

ultracapacitors. In recent years, the medical industry has been adopting the use of ultracapacitors for prosthetic applications [96, 97, 98, 99]. In these applications, the ultracapacitor is used as a stand-alone device, as the primary energy storage unit, to assist in the mechanical movement of a prosthetic leg. In addition to movement assistance, the ultracapacitor is also used to capture the regenerative energy generated during movement

(walking). This concept was extended to robotic applications by implementing regenerative energy-storing semi-active joints by using ultracapacitors as the stand-alone energy storage device [100].

Lastly, energy regeneration has also been applied to advanced exercise machine for use in the space environment or in the micro-gravity environment such as the International

Space Station (ISS). In these applications, ultracapacitors are used as a stand-alone energy storage devices to capture the user generated energy (regenerative energy) rather than dissipating it in passive elements. Reference [101], details such an advanced exercise machine in the form of a gym rowing machine with electro-mechanical energy conversion and modulation.

3.3.4 Summary of Findings and Conclusion

There are other markets for the ultracapacitor technology such as consumer electronics as well as various military, medical, and aerospace applications. The complete list of ultracapacitor applications is depicted in Table VIII. Within these major industries and primary markets, the ultracapacitor technology is implemented either as a standalone energy storage device or in a hybrid configuration with a primary energy source (battery,

combustion engine, or fuel cell). For the hybrid configuration, the usage of the ultracapacitor technology can be categorized in four groups: peak power assistance, back- up power and short-term emergency power, regenerative energy storage, and stand-alone energy storage (battery replacement) [80, 102].

In peak power assistance applications, ultracapacitors are utilized as either standalone energy storage devices or in combination with other primary energy sources such as batteries. In these applications, the ultracapacitor delivers a pulse of peak power while the primary energy source delivers the nominal, continuous energy to the load. This hybrid configuration reduces the electrical stress on the battery, thus extending its life-time.

In addition, the overall size of the battery is also reduced since the peak power requirements do not have to be supplied by the battery pack.

The second primary use of ultracapacitors is for temporary back-up power applications. In this type of application, the ultracapacitor supplies short-term emergency power to the load when the primary energy source fails. Regenerative energy storage was discussed extensively in Section 4.3.1. Lastly, ultracapacitors are used as stand-alone energy storage devices in applications where short-term energy is required.

TABLE VIII: INDUSTRY, MARKET DOMAIN, AND APPLICATIONS OF ULTRACAPACITORS

Table VIII summarizes the four primary categories of ultracapacitor usage correlated to various industries and markets. Hybrid energy storage systems composed of batteries and ultracapacitors are used in various energy storage applications; typical hybrid battery-ultracapacitor configurations are detailed in [95 and 103]. A generalized application model illustrating the use of ultracapacitors in a hybrid configuration is shown in Figure 43.

Figure 43: Application Model of Ultracapacitor Hybrid Energy Storage Systems.

Reprinted from [80]. Used with permission, Appendix D.

As illustrated in the application model of Figure 43, the ultracapacitor is able to receive energy from either the primary energy source or in some cases from the load

(regenerative braking applications). However, the ultracapacitor is not used for the sole purpose of re-charging the main power source, which is the specific application addressed in this dissertation. In addition, unlike the proposed ultrafast energy capture and high energy density storage system depicted in Figure 37, hybrid energy storage systems typically use ultracapacitors on the load side rather than the input/primary side of the energy storage system to provide load-transient electrical power. Furthermore, the literature review did not yield an applications similar to the application detailed in this dissertation, i.e. the use of ultracapacitors with the HILPB technology to capture high- pulses of intermittent optical energy and trickle-charging the primary energy source, on- board the all-electric MUAV.

CHAPTER IV

POWER SYSTEM DESIGN AND DEVELOPMENT IN SUPPORT OF HILPB

During the four-year tenure of AFRL-sponsored HILPB program, a total of three generations of end-to-end power systems were designed and built to support the research and development effort of the HILPB technology and its integration into the FQM-151A

Pointer Aircraft. The development of these end-to-end power systems are presented in this chapter.

4.1 1st Generation HILPB End-to-End Power System

The 1st generation end-to-end power system was designed to support the development of the HILPB technology with a secondary goal of eventually integrating the power system into the FQM-151A Pointer Aircraft at a later time. The power system was designed to control the flow of electrical energy from the VMJ photovoltaic solar cells to the downstream propulsion subsystem and the energy storage subsystem. Throughout the power system, electrical energy is monitored for system health and status purposes. The design incorporates an energy storage subsystem which includes specific battery charging

electronics for the Lithium-ion polymer (Li-Poly) batteries. The battery charging circuitry, features cell balancing electronics that provide charge/discharge accuracy and safety for the battery pack and for the energy storage subsystem. An illustrative block diagram of the 1st generation end-to-end HILPB power system shown in Figure 44.

Figure 44: 1st Generation End-to-End Power System Design in Support of HILPB

Power distribution through the system and to the load depends on the availability of the electrical energy from the VMJ cells and the status of the battery pack. In other words, the propulsion subsystem (MUAV’s brushless DC motor) may be powered directly from the VMJ cells through a buck/boost DC-to-DC converter or from the energy storage subsystem. The power system’s control circuitry allows either one of these two modes to be online or, if desirable, both modes may be offline, in which case the motor is powered off. An metal-oxide semiconductor field-effect transistor (MOSFET), the IRFU5305 manufactured by International Rectifier® (IR), long with a properly biased high voltage,

open-collector driver IC (Texas Instrument’s SN7406 series) ensures the correct functionality of the power systems’ control circuitry to properly route the available electrical energy.

System health and status circuitry tracks the flow of electrical energy throughout the power system, so that power distribution can be accurately controlled and displayed by the on-board controller. To this end, voltage and current measurements are taken at the following points in the system: the input power source generated by the VMJ photovoltaic cells (at the HILPB power receiver), the output of the buck/boost DC-to-DC converter, and the output of the energy storage subsystem. In addition, voltage and temperature measurements of each individual battery cell within the battery pack are also recorded. The battery charging circuitry provides additional health and status monitoring capabilities of the battery pack. A total of seven K-type thermocouples are used to monitor the temperature profile of the HILPB receiver and also the temperature of the battery pack.

The MAX6674, a temperature measurement integrated circuit (IC) which incorporates cold junction compensation, is used to measure temperatures in the range of 0 to 125 ⁰C; these temperatures are monitored by the on-board controller at a rate of once a second (1 Hz).

Measuring the flow of DC current through the power system is achieved using a high-side current sense amplifier – MAX4173H manufactured by Maxim Integrated™.

This IC uses an external current sense resistor, which was seized to optimize the current sense capability of this IC, based on the amount of maximum DC current flow. Hence,

MAX4173H produces an output voltage representative of the measured current. The output voltage of MAX4713H was conditioned using a low noise unity gain buffer amplifier and routed to the on-board controller.

Voltage measurement was achieved via a two-stage operational-amplifier design, which measured the bus voltage at different stages in the power system. The first op-amp stage is used as a high impedance follower, to minimize parasitic current draw or loading down of the bus voltage. The second circuit utilized another operational amplifier to precisely scale-down the bus voltage and provide the appropriate DC voltage to a 4- channel, 13-bit analog-to-digital converter. The analog-to-digital converter selected for this application was the AD7324 IC, a product of Analog Devices™. The operational amplifiers used in this design are of the Texas Instruments’ Burr-Brown® OPA251 family.

A block diagram of the voltage measurement circuitry and the current measurement circuitry is depicted in Figure 45.

Figure 45: Circuit Design – Voltage and Current Measurement

Controlling the electrical energy flow through the battery pack requires battery charging and battery discharging circuitry. Charging the battery pack is accomplished by using a highly integrated, multi-chemistry battery charger control IC. For the HILPB power system, the battery charring IC selected was the MAX1908, which is manufactured by Maxim Integrated™. In order to achieve high efficiency, MAX1908 utilizes a buck topology with synchronous rectification. With a few modifications, this battery charger may be configured to charge a variety of Lithium-based batteries at DC amperage charge rates as high as 7.5 Adc. MAX1908 uses analog inputs to control the charge voltage and charge current, which in turn gives the on-board controller flexibility and total control over these tasks. In addition, this battery charging IC make use of separate internal control compensation loops in order to achieve accurate voltage and current charging of the battery pack. Furthermore, this charger features additional system health and status monitoring capabilities, which are provided as outputs to the on-board controller. Some of the tasks that are monitored using this battery charging IC include: presence of the input-power, the battery-charging DC current, and the input DC amperage draw from the VMJ photovoltaic cells. Lastly, MAX1908 provides a battery charge/discharge feature that is dependent on the present state of the battery pack.

The energy storage subsystem incorporates balancing of individual battery cells during charging and discharging of the battery pack, to ensure that all cells within the battery pack have the same voltage potential during their fully charged state or fully discharged state. The individual battery cell balancing circuitry is required to ensure that the battery pack is in a balanced condition in case any of the individual battery cells reach their maximum charge state before the other cells. For optimal performance, the voltage

difference between the cells cannot be greater than 100 mV at any time during the charge or discharge cycles. In case the cells become unbalanced, the battery system’s efficiency is affected in two ways: first, the battery system has less capacity during the discharge cycle because the battery cell that is not fully charged will be drained before the other cells; second, once the battery system reaches an unbalanced state, the lifetime of the unbalanced battery cells is significantly reduced.

In order to balance the battery pack, each cell’s voltage is measured and recorded.

The individual cell voltage is measured by a precision, low drift, instrumentation amplifier

(Texas Instruments’ Burr-Brown® INA118). The voltage measurement accuracy of each battery cell is ensured by implementing a passive low-pass filter with an approximate cutoff frequency of 1.5 kHz to reduce sensitivity from high frequency noise. The output voltage of the INA118 is than polled by the A/D converter for digitization. Once the cell voltage is obtained, balancing or shunting a battery cell is achieved by redirecting a portion of the charging current (approximately 20%) around the battery cell through a power resistor.

The battery charging current is re-routed using a power FET (IRLR024N) connected in parallel with each individual cell. The power FETs, which are controlled by the on-board controller, along with the associated power resistors were used to balance the cells during charging and discharging of the battery pack. A block diagram of the energy storage subsystem’s functionality is depicted in Figure 46.

Figure 46: HILPB Power System – Block Diagram of the Battery Charging and Power

Management within the Energy Storage Subsystem

The intelligence of the HILPB power system is made possible by the on-board controller, a Xilinx Spartan-3 field programmable gate array (FPGA). In addition to data acquisition, interfacing with the battery charger IC, and all of the associated safety tasks previously described, the FPGA is also responsible with controlling the speed of the

MUAV’s propeller, controlling some of the power system’s tasks autonomously, interfacing with a wireless communication channel, and displaying the real-time data to a

Liquid Crystal Display (LCD); the LCD is used to quickly validate the status of the HILPB power system. The FPGA communicates with a remote computer through a 900 MHz,

9600 baud (Bd) rate, spread spectrum wireless module interface manufactured by

MaxStream Inc. The complete HILPB power system electronics have been designed to fit on a 5” by 8”, four layer printed circuit board (PCB), which is shown in Figure 47; the energy storage subsystem is illustrated in Figure 48.

Figure 47: HILPB Power System – Final Hardware Implementation

Figure 48: HILPB Power System – Energy Storage Subsystem

4.2 2nd Generation HILPB End-to-End Power System

A 2nd generation end-to-end power system was developed to further aid in the research and development efforts of the HILPB technology. The new HILPB power system featured improved data integrity and reliability along with improved capability and functionality, which allowed the ISSL team to automate testing in order to fully characterize the performance of the VMJ cells and the HILPB power receivers. The 2nd generation power system is composed of the following subsystems: a high-speed and high performance data acquisition subsystem, an active variable load used to trace the characteristic I-V curve of the VMJ photovoltaic cells, system health and status monitoring circuitry, and an on-board controller used for data processing and communication with a

personal computer (PC). A block diagram of the 2nd generation HILPB power system is depicted in Figure 49.

Figure 49: 2nd Generation HILPB End-to-End Power System

The 200-Watt HILPB power system depicted in Figure 49 and Figure 52 is capable of accepting an input power in the range of 9 Vdc to 28 Vdc and 3 Adc to 7 Adc. Similar to the first generation HILPB power system, the 2nd generation HILPB power system processes the unregulated electrical energy from the VMJ photovoltaic cells and provides regulated power to the propulsion subsystem and to the energy storage subsystem. The propulsion subsystem is primarily composed of the brushless DC motor along with the motor drive electronics required to propel the FQM-151A Pointer Aircraft. The energy storage subsystem is made up of a Li-Poly battery bank.

The HILPB power system was used extensively to characterize the performance of the VMJ photovoltaic cells. The typical I-V curves for the VMJ cells were generated using an active regulated DC electronic load. In general, photovoltaic cells have two modes of operation: voltage-regulation mode and current regulation mode. To test both operational modes of the VMJ photovoltaic cells, the electronic load was designed using two N- channel MOSFETs, which were operated in the linear region to mimic a variable resistor.

The MOSFET’s control circuitry was designed so that the two MOSFETs operate as a voltage source and as a current drain in order to generate the voltage-regulation mode and current regulation mode, respectively [104]. Since the MOSFETs operate in the linear region, the power dissipated in the MOSFETs internal resistance had to be dissipated in order to prevent damage to the power transistors. To this end, the thermal management strategy utilized a passive aluminum heat-sink along with an active fan to provide conduction cooling and convection cooling to ensure that the power MOSFETs do not exceed the manufacturer recommended junction temperature. The actively regulated DC- electronic load was designed, manufactured, and built in-house at the ISSL – the hardware is illustrated in Figure 50.

Figure 50: Actively Regulated Electronic Load for Photovoltaic Applications (I-V

Characteristic Curve Generation)

Voltage and current measuring circuitry have been designed to monitor the health and status of the power system. The analog sensing circuitry was improved from the 1st generation HILPB power system to achieve higher data accuracy and reliability. For example, the DC current is measured using Hall-Effect current sensors to reduce noise interference by isolating noisy circuitry from sensitive electronics. Similar to the 1st generation HILPB power system, the energy storage subsystem features charge balancing electronics, where power is actively routed through resistors that are in parallel with each individual battery cell to prevent overcharging of the battery pack. In addition, the voltage, current, and temperature of each individual battery cell is actively monitored. A block diagram of the improved sensing circuitry is illustrated in Figure 51.

Figure 51: 2nd Generation HILPB Power System – Block Diagram of the Sensing

Electronics and Overall System Functionality

One of the major improvements in the HILPB power system illustrated in Figure

49 is the high-speed data acquisition system (DATQ). At its core the DATQ implements a 200K-gate Xilinx Spartan-3 FPGA, which provides the necessary system controls along

with data logging and processing. To further improve the accuracy of the measured states throughout the power system, the data is represented by 16-bit words (19 bits effective).

This data is transmitted to the PC via the RS-232 interface at a rate of 6 Hz. Once the data was received by the PC, it was stored, plotted, and displayed by the PC using a custom

Graphical User Interface (GUI) that was written using the C programming language; the I-

V characteristic curve of the VMJ cells are plotted and displayed by the PC in real-time.

To further improve the noise immunity at the system-level, the HILPB power system hardware was divided into two separate PCBs. The 2nd generation HILPB end-to-end power system hardware is shown in Figure 52.

The 2nd generation HILPB end-to-end power system was used extensively in the research and development efforts of advancing the HILPB technology. The experimental results detailed in Section 2.3.1, Section 2.3.2, and Section 2.3.3 were performed using the end-to-end power management and data acquisition system illustrated in Figure 52.

Figure 52: 2nd Generation HILPB End-to-End Power System Hardware

4.3 Power Management and Distribution for the FQM-151A Aircraft

The experimental laboratory results demonstrated that the HILPB technology is mature and ready to be used in various applications that require wireless power transfer.

Depending on the specific application, the HILPB technology has to be tailored and packaged at the system-level in order to meet the specific application requirements. For the specific AFRL application detailed in this dissertation, the ISSL team packaged the

HILPB power receiver along with a custom PMAD system into the AFRL-supplied

MUAV. The MUAV platform selected by the AFRL for this program was the FQM-151A

Pointer Airplane manufactured by AeroVironment Inc. The selection was based on the wide use of small electric platforms by various branches of the U.S. military. FQM-151A

Pointer Airplane is a man-portable UAV designed with the mission of providing real-time video data surveillance information from the field of operation.

The U.S. Army and the Marine Corps operated the FQM-151A Pointer Airplane during the Operation Desert Storm in 1991. The radio-controlled aircraft implements a simple sail-plane configuration, which makes it lightweight and allows the military personnel to transport it to the field of operation and launch it by hand, as it is shown in

Figure 53. Depending on the specific mission requirements, the Pointer can be equipped with a night vision camera or other chemical-detection sensors. The video data is used for intelligence purposes and also by the operator in order to control the aircraft from the ground base. The aircraft’s specifications are detailed in Table IX [105, 106].

Figure 53: FQM-151A Pointer Airplane during Military Operations

TABLE IX: FQM-151A POINTER AIRCRAFT SPECIFICATION [105] Length 1.83 m (6 ft) Wingspan 2.74 m (9 ft) Weight 4.3 kg (9.6 lbs) Speed 80 km/h (43 knots) Ceiling 300 m (985 ft) Mission Radius 5 km (2.7 miles) Endurance Primary batteries: 60 minutes Propulsion 1 x Electric Motor (300 Watts) Max Speed 73 km/h (46 mph) Payload 0.74 kg (2 lbs)

A custom PMAD system was developed to be integrated into the FQM-151A

Pointer Aircraft. The custom PMAD system was designed to interface with a custom

HILPB power receiver and with the aircraft’s propulsion subsystem by controlling the power flow from the HILPB receiver and providing regulated power to the energy storage subsystem and to the propulsion subsystem. While the 1st generation and 2nd generation

HILPB end-to-end power systems detailed in Section 4.1 and Section 4.2, respectively, were developed primarily to serve as an engineering tool in support of HILPB during laboratory testing, this custom PMAD system was designed specifically for the FQM-151A

Pointer Aircraft. To this end, the PMAD system was designed to actively monitor and control the battery charging circuitry along with the power flow to the load and the battery pack. To accomplish these tasks, the PMAD system is divided into two subsystems: the battery charging subsystem and the command and data handling (C&DH) subsystem.

4.3.1 Battery Charging and Control Subsystem

The battery charging circuitry makes use of the MAX1535D [107], an advanced battery charger IC developed by Maxim® Integrated Products, to actively charge the battery pack and distribute power to the load. The MAX1535D evaluation kit [108] (see

Figure 54) was employed to speed up the design process; it is capable of charging one to four Li-ion cells with a total current of up to 8 Adc.

The MAX1535D is a versatile battery charger IC as it uses Intel’s System

Management Bus (SMBus™) protocol to interface with a microcontroller in order to actively control the charge voltage, charge current, and the maximum current drawn from the power source. By sending appropriate commands to the charger, these programmable parameters can be adjusted in real time. The input voltage to the charger IC can range from

8 Vdc to 28 Vdc, and it can supply a maximum charge voltage of approximately 19 Vdc to the battery pack.

The batteries are charged using a high-efficiency, synchronous-rectified, step-down

DC-DC converter, which enables the battery charger IC to operate as a precise constant- current and constant-voltage battery charger with input current limiting. The batteries are charged using the constant-current loop at first, followed by the constant voltage charge cycle. MAX1535D offers great accuracy and resolution: ±0.5% charge-voltage and ±0.5% input-current limit accuracy, 6-bit input-current and charge-current resolution, and an 11- bit charge-voltage resolution. Moreover, this IC also has a safety timer of 175 seconds which will disable charging if it is not re-enabled within that time frame; it acts as a watch dog timer to prevent over charging the battery pack.

Figure 54: Battery Charging Circuitry – MAXIM1535DEVKIT

4.3.2 Control and Data Handling Subsystem

The objective of the C&DH is to control the battery charging circuitry and to communicate and display the battery status information. The dsPICDEM 1.1 Plus

Development Board [109] from Microchip® (see Figure 55) is used to accomplish these tasks. It utilizes a 16-bit microcontroller, the dsPIC30F6014A [110], to control the Liquid

Crystal Display (LCD) and communicate with other peripherals such as the MAX1535D.

Figure 56 illustrates the hardware interface of the PMAD system which includes the

C&DH, the battery charging circuitry, the battery pack, and a power supply.

Figure 55: dsPICDEM 1.1 Plus Development Board and Additional Interface Hardware

Figure 56: Power Management and Distribution Subsystem’s Hardware Interface

The C&DH communicates with the battery charger IC using the SMBus™ protocol. As illustrated in Figure 57, the dsPICDEM 1.1 Plus Development Board’s LCD display along with the corresponding switches and potentiometers are used to control the battery charging circuitry while the LCD displays various system health and status parameters. Additional interface hardware is required between the ground station and the battery charging circuitry; this hardware has been mounted on the available bread-boarding area of the ground station as illustrated in Figure 55, and it consists of a high-side current sense IC, a buffer operational amplifier along as well as interface connectors and other passive components. MPLAP C30 compiler was used to program the dsPICDEM 1.1 Plus

Development Board.

Figure 57: The Control and Data Handling (C&DH) Subsystem’s Interface

4.3.3 Integration into the FQM-151A Pointer Aircraft

In order to use the HILPB technology with the MUAV, Dr. Daniel Raible of the

ISSL team designed and built a new HILPB power receiver for the FQM-151A Pointer

Aircraft. Recall from Section 2.2.4 that two types of HILPB power receivers were constructed during the HILPB research and development program at the ISSL. The first generation HILPB receiver implemented an air-cooled heat pipe thermal management system to remove the excess heat produced by the VMJ photovoltaic cell. The second generation HILPB receiver utilized an active thermal management system, which used water to remove the excess heat and keep the VMJ cell at nominal operating temperature.

Incorporating the HILPB receiver into the FQM-151A Pointer airframe, required a third

generation HILPB power receiver to be constructed using an air-cooled thermal management system with a closed-loop phase change fluid (nickel-plated heat pipe Zalman

CNPS9700-NT) due to weight and size constraints. The design and construction process for this HILPB power receiver are detailed in [2] and [3]. The ISSL team integrated the new HILPB power receiver into the FQM-151A Pointer Aircraft by making use of the aircraft’s center-tube, which passes through the receiver’s heat sink as illustrated in Figure

58.

Figure 58: HILPB Power Receiver Installed into the FQM-151A Pointer Aircraft [2, 3]

Upon integration of the new HILPB into the FQM-151A Pointer Aircraft, extensive testing was performed by beaming leaser power to the MUAV as illustrated in Figure 59.

The receiver is made up of nine (9) VMJ cells in parallel, which produced an electrical output of 2000 mAh at approximately 20 Vdc. The electrical power was routed through the payload bay with wire harnesses, which were connected to the PMAD system within the MUAV. At the end of the program with the AFRL, it was demonstrated experimentally that the HILPB technology is ready for a flight demonstration.

Figure 59: HILPB Research and Development Tests with the Pointer Aircraft at the

CSU’s ISSL High Intensity Laser Laboratory

Figure 60: HILPB Testing Set-Up using the HILPB End-to-End Power System,

Electronic Load, Personal Computer, Aircraft Gimbal System, and Laser System

CHAPTER V

SYSTEM MODELING, SIMULATON, AND DESIGN OPTIMIZATION

In Chapter V, the proposed ultrafast energy capture and high energy density storage system described in Section 3.2.1, is modeled, simulated, and optimized for a potential implementation on-board the MUAV for use in HILPB applications. To this end, the energy and power consumption requirements for the MUAV and a typical mission profile are first defined in Section 5.1. An optimization routine is developed mathematically in order to optimize the energy capture elements of the ultrafast energy capture and high energy density storage system. The development of a simulation model, the simulation results, and the duty cycle optimization of the intermittent energy pulses transmitted to the

MUAV are detailed in Section 5.3. Lastly, in Section 5.4, the ultrafast energy capture and high energy density storage system is further optimized to achieve maximum end-to-end power transfer efficiency. Section 5.4 also includes a sensitivity analysis to better understand how uncertainty in some parameters influence the system behavior.

5.1 Requirement Definition for the Energy Storage System On-Board the MUAV

In order to design and optimize the proposed ultrafast energy capture and high energy density storage system described in Section 4.2.1, the requirements for the energy storage subsystem on-board the MUAV must be defined. Section 4.3 details the integration of the HILPB power receiver and the PMAD system into the FQM-151 Pointer Airplane.

The energy storage system currently used on board the FQM-151, which was provided by the AFRL to the ISSL team, consists of six Li-polymer battery packs, capable of providing

22.2 Volts at 6 Ampere-hour. Each battery pack has three cells connected in series, which means that each Li-poly pack has a rating of 11.1 Volts (nominal) at 2 Ah. There are three packs connected in parallel in order to increase the system’s ampere rating to 6 Ah. These two parallel configurations are connected in series, which yield a nominal system voltage requirement of 22.2 Vdc. The approximate flight duration of the aircraft is approximately

60 minutes and the power requirements are as follows:

 Average Power: 111.2 Watts

 Cruise Power: 60.1 Watts

 Max Power at take-off: 257.2 Watts

During the past decade, however, the FQM-151 Pointer® Airplane was phased out by the manufacturer and replaced with the RQ-11B Raven® MUAV. The Raven is a man- portable MUAV and has similar but superior specifications to the FQM-151 Pointer

Airplane. The improvements over FQM-151 Pointer consists in the upgraded payload electronics to provide improved reconnaissance and surveillance capabilities. The RQ-

11B Raven® MAUV payload capabilities include: gimbaled high-resolution color electro-

optical (EO) camera and infra-red (IR) camera for night operations, digital stabilization, and thermal imager. RQ-11B Raven® MAUV is being used by all of the military services as it provides real-time situational awareness from the field of operations [111, 112]. The

Raven® UAV is illustrated in Figure 61.

Figure 61: Raven® RQ-11B MUAV. Courtesy of AeroVironment, Inc. (Used with

permission, Appendix D).

A literature review was performed to identify the specifications of the power plant for the RQ-11B Raven® MUAV. Although significant upgrades have been performed to the payload capability of the RQ-11B, the power plant has not seen any improvements from the FQM-151 Pointer® Airplane. The power plant specifications for the RQ-11B Raven®

MUAV has the following characteristics [113, 114, 115, 116]:

1) Battery chemistry: lithium-polymer

2) Maximum voltage (fully-charged): 25.2 Vdc

3) Minimum listed voltage: 21.0 Vdc

4) Capacity of the battery pack: 3.9 Amp-hour

From these specifications, it follows that the battery pack is made up of six individual battery cells as depicted by equation (5.1). The minimum voltage listed on the battery pack is 21.0 Vdc or 3.5 Vdc for each individual cell as illustrated in equation (5.2).

The RQ-11B Raven® UAV is programmed to automatically land if its battery reaches an extreme low voltage of 19.0 Vdc (or 3.0 Vdc per individual battery cell).

25.2 푉푑푐 퐼푛푑𝑖푣𝑖푑푢푎푙 퐵푎푡푡푒푟푦 퐶푒푙푙푠 = = 6 (5.1) 4.2 푉푑푐

21.0 푉푑푐 푀𝑖푛𝑖푚푢푚 퐿𝑖푠푡푒푑 퐶푒푙푙 푉표푙푡푎푔푒 = = 3.5 푉푑푐 (5.2) 6

The Li-ion polymer battery pack on-board the RQ-11B Raven MUAV was tested and characterized extensively in [115]. The characterization testing of the battery pack consisted of two tests: power consumption testing at each throttle position and endurance

testing based on a standard mission profile. The data depicting the amperage draw by the propulsion subsystem based on rising and falling throttle positions is depicted in Table X.

The battery endurance tests were based on a typical mission profile based on recommendations from the manufacturer (AeroVironment) and the Naval Air System

Command. The mission profile is characterized by two major states: altitude climbing, with a throttle level of 100% for approximately 20 seconds, and normal operation on autopilot (MUAV operating at 300-500 ft) with a throttle level of 55%. The duration of the altitude climbing mode is approximately 20 seconds. Hence, the battery was tested by setting the throttle level to 100% for 20 seconds followed by a throttle level of 55% until the battery reached 21.9 Vdc; the low-charge indicator allows the MUAV to fly for an additional 10-to-15 minutes in order to allow the possibility of its return to base. The battery endurance tests were performed on two separate batteries; the test results are illustrated in Figure 62 and Figure 63 depicting the batteries’ voltage and amperage measurements, respectively. The test results indicated that the average operational duration was 126 minutes, which is 36 minutes longer than the advertised manufacturer specifications [115].

TABLE X: POWER CONSUMPTION DATA FOR THE RAVEN UAV DURING INCREASING AND DECREASING THROTTLE POSITIONS [115] Increasing Throttle Decreasing Throttle Throttle Position % Current Demand (Adc) Current Demand (Adc) 25 0.35 0.35 30 0.48 0.44 35 0.61 0.57 40 0.74 0.71 45 0.9 0.9 50 1.06 1.03 55 1.22 1.21 60 1.38 1.35 65 1.56 1.56 70 1.8 1.83 75 2.14 2.11 80 2.52 2.55 85 3 2.97 90 3.33 3.39 95 3.96 3.9 100 6.14 6.14

Figure 62: Raven® RQ-11B Battery Endurance Tests – Voltage Measurements [115]

Figure 63: Raven® RQ-11B Battery Endurance Tests – Amperage Measurements [115]

As outlined in Section 4.2.1, the goal is to design and develop an energy storage system that will meet the MUAV’s energy storage requirements outlined above and enable the application of HILPB to beam power to the MUAV while eliminating the practical limitation of tracking the MUAV with a laser beam for tens of minutes. To this end, the number of optimal number of ultracapacitors must be determined in order to capture the intermittent energy pulses from the VMJ photovoltaic cells via the optical directed energy

(laser) system. The next section presents a methodology to optimize the number of ultracapacitors on-board the MUAV based on the energy storage requirements outlined above.

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5.2 Development of an Optimization Routine for the Energy Capture Elements

The HILPB experimental laboratory results detailed in Chapter 2 demonstrate that the HILPB technology is mature and ready to be used in various applications. For the

MUAV application, the primary objective is to minimize the intermittent pulses of optical energy beamed to the aircraft. To this end, the front-end of the proposed ultrafast energy capture and high energy density storage system described in Section 4.2.1 is of utmost importance since it is used to capture the high energy pulses. Therefore, in order to size and design the front-end portion of the ultrafast energy capture and high energy density storage system, an optimization routine is developed to be used as a design tool. This design tool is used to select the appropriate ultracapacitor from a database of available products and to size the ultracapacitor bank, i.e. number of ultracapacitors in series and parallel configurations.

5.2.1 Objective Function Derivation

Minimizing the frequency of the intermitted laser pulses transmitted to the aircraft via the HILPB technology is dependent on the ability of the hybrid energy storage system on-board the aircraft to capture the directed optical energy, i.e. how much energy can be captured and how fast. The portion of the energy storage system that is directly linked to capturing the intermitted laser pulses is the ultracapacitor bank.

The frequency of intermitted optical energy pulses that must be beamed to the aircraft within a period of 60 minutes is defined by equation (5.3), where 퐸푈퐴푉푐푟푢𝑖푠푒 is the

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energy required by the aircraft to maintain cruising altitude and 퐸푈퐶푢푠푎푏푙푒 is the usable energy of the ultracapacitor bank after taking into account the energy losses associated with discharging the ultracapacitor bank and transferring the energy to the battery pack.

퐸푈퐴푉푐푟푢𝑖푠푒 퐹퐻퐼퐿푃퐵 = (5.3) 퐸푈퐶푏푎푛푘푈푠푎푏푙푒

The energy required by the aircraft to maintain cruising altitude 퐸푈퐴푉푐푟푢𝑖푠푒 is dependent on the power required by the motor, the flight duration, and the energy capacity of the battery pack. The propulsion subsystem detailed in Section 5.1, is a 60-Watt brushless DC motor and the flight duration for this application is specified at 60 minutes. In addition, the energy capacity the 25.2 Vdc rechargeable Li-ion polymer battery pack powering the

MUAV is approximately 98 Watt-hours [113] as depicted by equation (5.4). It follows that the energy required for the RQ-11B Raven MUAV to maintain cruising altitude is approximately 353,808 Joules.

퐸푈퐴푉푐푟푢𝑖푠푒 = 퐸퐵푎푡푡푒푟푦 = 푉퐵푎푡푡푒푟푦푃푎푐푘 ∙ 퐶ℎ푎푟푔푒퐵푎푡푡푒푟푦푃푎푐푘 (5.4) = 25.2 푉푑푐 × 3.9 퐴푚푝 ∙ 퐻표푢푟 = 353,808 퐽표푢푙푒푠

Extensive research was performed to determine the equations needed to size the ultracapacitor bank. A literature review was performed to identify methodologies used to size an ultracapacitor bank. The best methods that describe how to size an ultracapacitor bank are [117] and [118]. The method described in these references are derived using a single ultracapacitor with a focus on determining the total number of ultracapacitors. This dissertation takes a different approach, however, by defining the system-level equations while also taking into account the series and parallel strings of ultracapacitors. The mathematical derivation of the equations needed to size the ultracapacitor bank for the

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ultrafast energy capture and high energy density storage system is detailed in the next sub- section.

Sizing the Ultracapacitor Bank for Ultrafast Energy Capture and High Energy Density

Applications

In an ideal case, the energy available in an ultracapacitor bank is a function of the equivalent capacitance in an ultracapacitor system and its maximum voltage:

1 퐸 = 퐶 푉2 (5.5) 푈퐶푏푎푛푘 2 푒푞푢𝑖푣푎푙푒푛푡 푆푦푠푡푒푚푀푎푥

The usable energy available in an ultracapacitor bank is dependent on the discharge ratio 푑푠푦푠푡푒푚, which is defined as the minimum allowed voltage 푉푆푦푠푡푒푚푀𝑖푛 (once the discharge of the ultracapacitor bank is complete) and the maximum voltage of the ultracapacitor bank 푉푆푦푠푡푒푚푀푎푥. The discharge ratio 푑푠푦푠푡푒푚 is defined in (5.7).

1 1 퐸 = 퐶 푉2 − 퐶 푉2 (5.6) 푈퐶푏푎푛푘푈푠푎푏푙푒 2 푒푞푢𝑖푣푎푙푒푛푡 푆푦푠푡푒푚푀푎푥 2 푒푞푢𝑖푣푎푙푒푛푡 푆푦푠푡푒푚푀𝑖푛

푉푆푦푠푡푒푚푀𝑖푛 푑푠푦푠푡푒푚 = ∙ 100 (5.7) 푉푆푦푠푡푒푚푀푎푥

It follows that the usable energy of the ultracapacitor bank defined in (5.6) is expanded as a function of the discharge ratio:

2 1 푑푠푦푠푡푒푚 퐸 = 퐶 푉2 ∙ [1 − ( ) ] (5.8) 푈퐶푏푎푛푘푈푠푎푏푙푒 2 푒푞푢𝑖푣푎푙푒푛푡 푆푦푠푡푒푚푀푎푥 100

When energy is extracted from the ultracapacitor bank, there is energy that is lost in the form of heat due to the internal resistance of the ultracapacitors. Therefore, the usable

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energy from an ultracapacitor bank is dependent on the efficiency associated with discharging the ultracapacitor with a constant current and the efficiency of the DC-to-DC converter that transfers the energy from the ultracapacitor bank to the battery pack.

퐸푈퐶푏푎푛푘푈푠푎푏푙푒퐷𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 퐸푈퐶푏푎푛푘푈푠푎푏푙푒 ∙ 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 ∙ 휂퐷퐶/퐷퐶 (5.9)

Efficiency Loss when Discharging the Ultracapacitor Bank with Constant Current

The efficiency associated with discharging the ultracapacitor with a constant current is dependent on the internal resistance and the amount of DC current that is being extracted. The DC current being extracted from an ultracapacitor system is defined in equation (5.10). From equation (5.10), the voltage variation across a system of ultracapacitors is derived as sown in (5.11).

∆푉푠푦푠푡푒푚 𝑖푆푦푠푡푒푚 = 퐶푒푞푢𝑖푣푎푙푒푛푡 ∙ (5.10) ∆푡푑𝑖푠푐ℎ푎푟𝑔푒

𝑖푆푦푠푡푒푚 ∆푉푠푦푠푡푒푚 = ∙ ∆푡푑𝑖푠푐ℎ푎푟𝑔푒 (5.11) 퐶푒푞푢𝑖푣푎푙푒푛푡

The voltage 푉푠푦푠푡푒푚 across a system of ultracapacitors is dependent on the maximum voltage 푉푆푦푠푡푒푚푀푎푥 across a system of ultracapacitors [117]:

𝑖푆푦푠푡푒푚 푉푠푦푠푡푒푚 = 푉푆푦푠푡푒푚푀푎푥 − ∙ 푡푑𝑖푠푐ℎ푎푟𝑔푒 (5.12) 퐶푒푞푢𝑖푣푎푙푒푛푡

푑 The time to discharge the ultracapacitor bank from 푉 to 푉 ∙ 푆푦푠푡푒푚 is 푆푦푠푡푒푚푀푎푥 푆푦푠푡푒푚푀푎푥 100 derived as follows:

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푑푆푦푠푡푒푚 𝑖푆푦푠푡푒푚 푉푆푦푠푡푒푚푀푎푥 ∙ = 푉푆푦푠푡푒푚푀푎푥 − ∙ 푡푑𝑖푠푐ℎ푎푟𝑔푒 100 퐶푒푞푢𝑖푣푎푙푒푛푡

푑푆푦푠푡푒푚 𝑖푆푦푠푡푒푚 푉푆푦푠푡푒푚푀푎푥 ∙ (1 − ) = ∙ 푡푑𝑖푠푐ℎ푎푟𝑔푒 100 퐶푒푞푢𝑖푣푎푙푒푛푡

푉푆푦푠푡푒푚푀푎푥 푑푆푦푠푡푒푚 푡푑𝑖푠푐ℎ푎푟𝑔푒 = 퐶푒푞푢𝑖푣푎푙푒푛푡 ∙ ∙ (1 − ) 𝑖푆푦푠푡푒푚 100

푉푆푦푠푡푒푚푀푎푥 100 − 푑푆푦푠푡푒푚 푡푑𝑖푠푐ℎ푎푟𝑔푒 = 퐶푒푞푢𝑖푣푎푙푒푛푡 ∙ ∙ (5.13) 𝑖푆푦푠푡푒푚 100

The energy loss due to the equivalent series resistance 푅푆푒푟𝑖푒푠퐸푞푢𝑖푣푎푙푒푛푡 of the ultracapacitor bank can be expressed as the accumulation of the internal power being dissipated [117]:

푡 퐸푈퐶퐿표푠푠푅푠푒 = ∫ 푃푆푒푟𝑖푒푠푅푒푠𝑖푠푡푎푛푐푒 ∙ 푑푡 0

푡 2 퐸푈퐶퐿표푠푠푅푠푒 = ∫ 푅푆푒푟𝑖푒푠퐸푞푢𝑖푣푎푙푒푛푡 ∙ 𝑖푠푦푠푡푒푚 ∙ 푑푡 0

2 퐸푈퐶퐿표푠푠푅푠푒 = 푅푆푒푟𝑖푒푠퐸푞푢𝑖푣푎푙푒푛푡 ∙ 𝑖푠푦푠푡푒푚 ∙ 푡푑𝑖푠푐ℎ푎푟𝑔푒 (5.14)

Incorporating the discharge time defined in (5.13) into equation (5.14) yields:

푉 100 − 푑 2 푆푦푠푡푒푚푀푎푥 푆푦푠푡푒푚 퐸푈퐶퐿표푠푠푅푠푒 = 푅푆푒푟𝑖푒푠퐸푞푢𝑖푣푎푙푒푛푡 ∙ 𝑖푠푦푠푡푒푚 ∙ 퐶푒푞푢𝑖푣푎푙푒푛푡 ∙ ∙ 𝑖푆푦푠푡푒푚 100

퐸푈퐶퐿표푠푠푅푠푒 = 푅푆푒푟𝑖푒푠퐸푞푢𝑖푣푎푙푒푛푡 ∙ 𝑖푆푦푠푡푒푚 ∙ 퐶푒푞푢𝑖푣푎푙푒푛푡 ∙ 푉푆푦푠푡푒푚푀푎푥 (5.15) 100 − 푑푆푦푠푡푒푚 ∙ 100

The total energy that can be extracted from the ultracapacitor bank, taking into account the usable energy as a function of the discharge ratio and the energy loss associated with the

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internal series resistance (while discharging the ultracapacitor bank with a constant current) is given by:

퐸푈퐶푇표푡푎푙퐿표푎푑 = 퐸푈퐶푏푎푛푘푈푠푎푏푙푒 − 퐸푈퐶푙표푠푠푅푠푒 (5.16)

Equation (5.16) is used to define the energy efficiency as a function of the discharge current:

퐸푈퐶푇표푡푎푙퐿표푎푑 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 퐸푈퐶푏푎푛푘푈푠푎푏푙푒

퐸푈퐶푏푎푛푘푈푠푎푏푙푒 − 퐸푈퐶푙표푠푠푅푠푒 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 퐸푈퐶푏푎푛푘푈푠푎푏푙푒

휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 =

2 1 푑푠푦푠푡푒푚 100−푑푆푦푠푡푒푚 퐶 푉2 ∙[1−( ) ]−푅 ∙𝑖 ∙퐶 ∙푉 ∙ 2 푒푞푢𝑖푣푎푙푒푛푡 푆푦푠푡푒푚푀푎푥 100 푆푒푟𝑖푒푠퐸푞푢𝑖푣푎푙푒푛푡 푆푦푠푡푒푚 푒푞푢𝑖푣푎푙푒푛푡 푆푦푠푡푒푚푀푎푥 100 2 1 푑푠푦푠푡푒푚 퐶 푉2 ∙[1−( ) ] 2 푒푞푢𝑖푣푎푙푒푛푡 푆푦푠푡푒푚푀푎푥 100

2 1 2 푑푠푦푠푡푒푚 2 퐶푒푞푢𝑖푣푎푙푒푛푡푉푆푦푠푡푒푚푀푎푥 ∙ [1 − ( 100 ) ] 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 2 1 2 푑푠푦푠푡푒푚 2 퐶푒푞푢𝑖푣푎푙푒푛푡푉푆푦푠푡푒푚푀푎푥 ∙ [1 − ( 100 ) ]

100 − 푑푆푦푠푡푒푚 푅푆푒푟𝑖푒푠퐸푞푢𝑖푣푎푙푒푛푡 ∙ 𝑖푆푦푠푡푒푚 ∙ 퐶푒푞푢𝑖푣푎푙푒푛푡 ∙ 푉푆푦푠푡푒푚푀푎푥 ∙ 100 − 2 1 2 푑푠푦푠푡푒푚 2 퐶푒푞푢𝑖푣푎푙푒푛푡푉푆푦푠푡푒푚푀푎푥 ∙ [1 − ( 100 ) ]

휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶

100 − 푑푆푦푠푡푒푚 푅푆푒푟𝑖푒푠퐸푞푢𝑖푣푎푙푒푛푡 ∙ 𝑖푆푦푠푡푒푚 ∙ 퐶푒푞푢𝑖푣푎푙푒푛푡 ∙ 푉푆푦푠푡푒푚푀푎푥 ∙ 100 (5-17) = 1 − 2 1 2 푑푠푦푠푡푒푚 2 퐶푒푞푢𝑖푣푎푙푒푛푡푉푆푦푠푡푒푚푀푎푥 ∙ [1 − ( 100 ) ]

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It is known that the total capacitance and the total resistance at the ultracapacitor system level is dependent on the number of individual ultracapacitors in series and parallel [119].

# 푝푎푟푎푙푙푒푙 푁푝 퐶푒푞푢𝑖푣푎푙푒푛푡 = 퐶푐푒푙푙 ∙ = 퐶푐푒푙푙 ∙ (5-18) # 푠푒푟𝑖푒푠 푁푠

# 푠푒푟𝑖푒푠 푁푠 푅푆푒푟𝑖푒푠퐸푞푢𝑖푣푎푙푒푛푡 = 푅푐푒푙푙 ∙ = 푅푐푒푙푙 ∙ (5-19) # 푝푎푟푎푙푙푒푙 푁푝

The energy efficiency can now be expressed as a function of individual ultracapacitors in series and parallel:

푁푠 푁푝 100 − 푑푆푦푠푡푒푚 푅푐푒푙푙 ∙ ∙ 𝑖푆푦푠푡푒푚 ∙ 퐶푐푒푙푙 ∙ ∙ 푉푆푦푠푡푒푚푀푎푥 ∙ 푁푝 푁푠 100 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 1 − 2 1 푁푝 2 푑푠푦푠푡푒푚 ∙ 퐶푐푒푙푙 ∙ ∙ 푉푆푦푠푡푒푚푀푎푥 ∙ [1 − ( ) ] 2 푁푠 100

푁푠 100 − 푑푆푦푠푡푒푚 푅푐푒푙푙 ∙ ∙ 𝑖푆푦푠푡푒푚 ∙ 푁푝 100 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 1 − 2 1 푑 ∙ 푉 ∙ [1 − ( 푠푦푠푡푒푚) ] 2 푆푦푠푡푒푚푀푎푥 100

100 − 푑푆푦푠푡푒푚 2 ∙ 푅푐푒푙푙 ∙ 𝑖푆푦푠푡푒푚 ∙ 푁푠 100 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 1 − ∙ 2 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 푑푠푦푠푡푒푚 [1 − ( 100 ) ]

100 푑 − 푆푦푠푡푒푚 2 ∙ 푅푐푒푙푙 ∙ 𝑖푆푦푠푡푒푚 ∙ 푁푠 100 100 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 1 − ∙ 2 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 1002 푑 − 푠푦푠푡푒푚 1002 1002

100 − 푑푆푦푠푡푒푚 2 ∙ 푅푐푒푙푙 ∙ 𝑖푆푦푠푡푒푚 ∙ 푁푠 100 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 1 − ∙ 2 2 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 100 − 푑푠푦푠푡푒푚 1002

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2 2 ∙ 푅푐푒푙푙 ∙ 𝑖푆푦푠푡푒푚 ∙ 푁푠 100 − 푑푆푦푠푡푒푚 100 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 1 − ∙ ∙ 2 2 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 100 100 − 푑푠푦푠푡푒푚

2 ∙ 푅푐푒푙푙 ∙ 𝑖푆푦푠푡푒푚 ∙ 푁푠 100 − 푑푆푦푠푡푒푚 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 1 − ∙ 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 100

1002 ∙ 2 2 (100 − 푑푆푦푠푡푒푚) ∙ (100 + 푑푆푦푠푡푒푚)

2 ∙ 푅푐푒푙푙 ∙ 𝑖푆푦푠푡푒푚 ∙ 푁푠 100 − 푑푆푦푠푡푒푚 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 1 − ∙ 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 100

1002 ∙ (100 − 푑푆푦푠푡푒푚) ∙ (100 + 푑푆푦푠푡푒푚)

2 ∙ 푅푐푒푙푙 ∙ 푁푠 ∙ 𝑖푆푦푠푡푒푚 100 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 1 − ∙ (5-20) 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 100 + 푑푆푦푠푡푒푚

5.2.2 Formulating the Objective Function

From equation (5-9), recall that the total energy that can be extracted from the ultracapacitor bank, is dependent on the efficiency associated with discharging the ultracapacitor with a constant current and the efficiency of the DC-to-DC converter that transfers the energy from the ultracapacitor bank to the battery pack.

퐸푈퐶푏푎푛푘푈푠푎푏푙푒퐷𝑖푠푐ℎ푎푟𝑔푒퐶퐶 = 퐸푈퐶푏푎푛푘푈푠푎푏푙푒 ∙ 휂푑𝑖푠푐ℎ푎푟𝑔푒퐶퐶 ∙ 휂퐷퐶/퐷퐶

The efficiency of the DC-to-DC converter is assumed to be approximately 85% and is independent on the ultracapacitor bank.

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퐸푈퐶푏푎푛푘푈푠푎푏푙푒퐷𝑖푠푐ℎ푎푟𝑔푒퐶퐶

2 1 푑푠푦푠푡푒푚 = ( ∙ 퐶 ∙ 푉2 ∙ [1 − ( ) ]) 2 푒푞푢𝑖푣푎푙푒푛푡 푆푦푠푡푒푚푀푎푥 100 (5-21)

2 ∙ 푅푐푒푙푙 ∙ 푁푠 ∙ 𝑖푆푦푠푡푒푚 100 ∙ (1 − ∙ ) ∙ (0.85) 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 100 + 푑푆푦푠푡푒푚

The numerator can also be expressed using individual ultracapacitors in series and parallel:

퐸푈퐶푏푎푛푘푈푠푎푏푙푒퐷𝑖푠푐ℎ푎푟𝑔푒퐶퐶

2 1 푁푝 2 푑푠푦푠푡푒푚 = ( ∙ 퐶푐푒푙푙 ∙ ∙ 푉푆푦푠푡푒푚푀푎푥 ∙ [1 − ( ) ]) 2 푁푠 100 (5-22)

2 ∙ 푅푐푒푙푙 ∙ 푁푠 ∙ 𝑖푆푦푠푡푒푚 100 ∙ (1 − ∙ ) ∙ (0.85) 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 100 + 푑푆푦푠푡푒푚

Substituting (5-21) into (5-3), the frequency of intermitted laser energy pulses that must be beamed to the aircraft becomes:

퐸푈퐴푉푐푟푢𝑖푠푒 퐹퐻퐼퐿푃퐵 = 2 1 푁푝 2 푑푠푦푠푡푒푚 ( ∙ 퐶푐푒푙푙 ∙ ∙ 푉푆푦푠푡푒푚푀푎푥 ∙ [1 − ( ) ]) ∙ 2 푁푠 100 (5-23) 2 ∙ 푅 ∙ 푁 ∙ 𝑖 100 (1 − 푐푒푙푙 푠 푆푦푠푡푒푚 ∙ ) ∙ (0.85) 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 100 + 푑푆푦푠푡푒푚

Therefore, (5-23) may be used as the objective optimization function, where the objective is to minimize the frequency of intermitted laser pulses:

퐸푈퐴푉푐푟푢𝑖푠푒 푚𝑖푛퐹퐻퐼퐿푃퐵 = 2 1 푁푝 2 푑푠푦푠푡푒푚 ( ∙ 퐶푐푒푙푙 ∙ ∙ 푉푆푦푠푡푒푚푀푎푥 ∙ [1 − ( ) ]) ∙ 2 푁푠 100 (5-24) 2 ∙ 푅 ∙ 푁 ∙ 𝑖 100 (1 − 푐푒푙푙 푠 푆푦푠푡푒푚 ∙ ) ∙ (0.85) 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 100 + 푑푆푦푠푡푒푚

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Since 퐸푈퐴푉푐푟푢𝑖푠푒 is a constant, equation (5-24) becomes a function of maximizing the denominator:

푚푎푥퐸푈퐶푏푎푛푘푈푠푎푏푙푒퐷𝑖푠푐ℎ푎푟𝑔푒퐶퐶

2 1 푁푝 2 푑푠푦푠푡푒푚 = ( ∙ 퐶푐푒푙푙 ∙ ∙ 푉푆푦푠푡푒푚푀푎푥 ∙ [1 − ( ) ]) 2 푁푠 100 (5-25)

2 ∙ 푅푐푒푙푙 ∙ 푁푠 ∙ 𝑖푆푦푠푡푒푚 100 ∙ (1 − ∙ ) ∙ (0.85) 푁푝 ∙ 푉푆푦푠푡푒푚푀푎푥 100 + 푑푆푦푠푡푒푚 where the design parameters are defined as follows:

 푉푐푒푙푙 is the voltage of an individual ultracapacitor cell

 퐶푐푒푙푙 is the capacitance of an individual ultracapacitor cell

 푅푐푒푙푙 is the internal resistance of an individual ultracapacitor cell

 푉푆푦푠푡푒푚푀푎푥 is the maximum voltage of the ultracapacitor bank

The search variables of the objective function are defined as follows:

 discharge ratio of the ultracapacitor system: 푑푠푦푠푡푒푚

 discharge current of the ultracapacitor system: 𝑖푠푦푠푡푒푚

 the number of ultracapacitors in series: 푁푠

 the number of ultracapacitors in parallel: 푁푝

The constraints of the objective function are defined as follows:

 Discharge ratio (%):

푀𝑖푛𝑖푚푢푚 퐷𝑖푠푐ℎ푎푟푔푒 푅푎푡𝑖표 ≤ 푑푠푦푠푡푒푚 ≤ 푀푎푥𝑖푚푢푚 퐷𝑖푠푐ℎ푎푟푔푒 푅푎푡𝑖표

 Maximum discharge current from the ultracapacitor bank (Adc):

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𝑖푠푦푠푡푒푚 ≤ 푀푎푥𝑖푚푢푚 퐷𝑖푠푐ℎ푎푟푔푒 퐶푢푟푟푒푛푡

 Maximum allowable mass, i.e. weight constraint (kg):

푁푠 ∙ 푁푝 ∙ 푀푎푠푠푈푙푡푟푎푐푎푝푎푐𝑖푡표푟 ≤ 푇표푡푎푙 푀푎푠푠

 Maximum number of ultracapacitors in series:

푉푆푦푠푡푒푚푀푎푥 푁푠 ≤ 푉푐푒푙푙

 Maximum number of series ultracapacitors in parallel:

푁푝 ≤ 푀푎푥𝑖푚푢푚 푁푢푚푏푒푟 표푓 푆푒푟𝑖푒푠 푆푡푟𝑖푛푔푠

5.2.3 Implementation of the Optimization Routine

The goal of the optimization function is to minimize the frequency of intermitted laser pulses by maximizing the objective function in equation (5-24). The objective function, the search variables, and optimization constraints defined in Section 5.2.2 were implemented using MathWorks® Matlab via three separate “.m” files: Appendix D details the “.m” file containing the objective function; Appendix E details the “.m” file containing the constraints for the objective function; and Appendix C details a third “.m” file that initializes all variables and calls the objective and constraints functions.

From a practical perspective, the objective function was expanded to include a database of viable ultracapacitors that could be used for this application. A thorough research was performed of ultracapacitor from various manufacturers that could be used for this application. The selected ultracapacitors were tabulated into a database with the following corresponding information: manufacturer, product name, voltage, capacitance,

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equivalent series resistance (ESR), mass, length, and diameter; the ultracapacitor database is depicted in Table XI.

TABLE XI: DATABASE OF AVAILABLE ULTRACAPACITORS

A global optimization algorithm was selected for the optimization routine in order to find the global optimum point of the objective function that is given by equation (5-25) and implemented as detailed in Appendix D. To this end, the genetic algorithm (GA) method was selected because due to its ability to solve constrained and unconstrained optimization problems. The goal was to have the GA search the database of available components depicted in Table XI and find the optimal ultracapacitor for the ultrafast energy capture and high energy density application based on the available ultracapacitors and their respective variables: capacitance, voltage, ESR, and weight. To this end, as defined in the

Matlab program detailed in Appendix C, the GA uses the component indices in order to index into the database vectors of component values from Table XI.

Furthermore, the optimization routine is user-interactive as it has been programmed into Matlab with the goal of using it for other applications. For example, after running the

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primary Matlab program detailed in Appendix C, the Matlab Command Window prompts the user to enter the mass constraint in kilograms (the user enters the desired mass constraint by pressing the “Enter” key on the keyboard). Depending on the weight constraint entered by the user in the Matlab Command Window, the objective function reaches the optimum point by selecting the optimum ultracapacitor part number from the database. Once the desired mass for the entire ultracapacitor bank is entered, the optimization routine yields the optimum design information for the ultracapacitor bank including:

 The optimal ultracapacitor to be used for the application, i.e. the line item number

from the database shown in Table XI

 The optimal number of ultracapacitors in parallel: 푁푝

 The optimal number of ultracapacitors in series: 푁푠

 The optimal discharge ratio of the ultracapacitor bank: 푑푠푦푠푡푒푚

 The optimal amplitude of the discharge current: 𝑖푠푦푠푡푒푚

The volume of the ultracapacitor bank was considered as an additional constraint to the objective function. However, all ultracapacitors would be arranged in a side-by-side matrix of cylinders and connected with wire harnesses. Hence, adding volume as a constraint would not add value to the objective function.

5.2.4 Optimization Results using Genetic Algorithms

Once the optimization routine was successfully implemented using MathWorks’

Matlab, the constraints for the MUAV were set as follows:

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 Discharge ratio (%): minimum of 20 % and maximum of 80 %

 Maximum discharge current from the ultracapacitor bank: 3 Adc

 Maximum allowable mass, i.e. weight constraint (kg): user defined in the Matlab

Command Window

 Maximum number of ultracapacitors in series: 10

 Maximum number of series ultracapacitors in parallel: 3

An example of the user-interactive optimization result is illustrated in Figure 64. After the

Matlab program is executed, a message is displayed in the Command Window prompting the user to enter the mass constraint for the ultracapacitor bank. Once the mass constraint is entered, the optimizer uses the search variables to find the optimum result. The convergence process of the GA is illustrated in Figure 65.

The results of the GA optimizer for this case are detailed in Table XII. The total mass of the ultracapacitor bank was varied from 1 kg to 5 kg in increments of 0.5 kg. Based on the results from Table XII, it was concluded that the optimal ultracapacitor is the

FastCap EEx3V-450 (line item #1 in Table XI) for applications where the mass of the ultracapacitor bank cannot exceed 2 kg. For MUAVs that can handle a heavier payload, the optimal capacitor is Maxwell’s K2. Furthermore, various combinations of series and parallel ultracapacitors were generated depending on the total weight of the ultracapacitor bank.

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Figure 64: User-Interactive Optimization Routine via the Matlab Command Window

Figure 65: Optimization Routine Convergence Plot During the GA Optimization

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TABLE XII: OPTIMIZATION RESULTS USING THE GENETIC ALGORITHM OPTIMIZER

The optimization results from Table XII vary based on the initial population created by the GA. According to the optimization results from Table XII, the discharge ratio of the ultracapacitor bank reached the maximum boundary of 20%. In order words, the ultracapacitor bank must be discharged to its maximum level in order to extract the most energy. The discharge current from the ultracapacitor bank is recommended in order to minimize the energy loss to the ultracapacitor internal equivalent series resistance (ESR).

For the specific application discussed in this dissertation, the FQA-151A Pointer® and the

RQ-11B Raven® MUAVs have limited mass allocations for the energy storage system.

Therefore, for a maximum mass allocation of 1 kg for the energy storage system, the optimal solution is represented by row #1 in Table XII.

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5.3 Model Development, Simulation, and Duty Cycle Optimization

The experimental laboratory results demonstrated that the HILPB technology is mature and ready to be applied to various applications. The development of the proposed hybrid energy storage system is based on the hypothesis that the MUAV’s on-board Li-

Poly batteries can be re-charged from the electrical energy captured by the bank of ultracapacitors, which is also on-board the MUAV. Therefore, theoretically given the hybrid configuration depicted in Figure 37, the ultracapacitor could be used to trickle- charge the main power source via a buck-boost DC-DC converter.

5.3.1 Simulation Environment and Component Models

A thorough research was performed to assess and select the appropriate simulation platform required to design and simulate the ultrafast energy capture and high electrical energy density storage subsystem along with the complete PMAD system. The simulation environments considered as candidates included: SIMetrix/SIMPLIS®, LTspice®,

PowerSIM (PSIM®), and Matlab® Simulink®. The assessment was based on the availability of the following simulation models: ultracapacitor, battery, DC-to-DC converter, and active load capability. PSIM® and Matlab™ Simulink™ are the only two environments that meet the requirements for the desired simulation models. While PSIM is a great tool to simulate power system and power electronics, Matlab Simulink was selected as the simulation platform due to its capability to couple various optimization algorithms available in the Matlab environment with the behavioral simulation model.

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There are two simulation platforms available within the Matlab Simulink environment: Simulink’s Simscape™ Electronics™ and Simulink Simscape™ Power

Systems™. Simulation models were constructed in both platforms for evaluation purposes.

The Simscape Power Systems toolbox offers better models for ultracapacitor and Li-ion battery components. However, the Simulink Simscape Power Systems Toolbox is developed by a third party contracted by MathWorks and does not easily interface with the

Simscape Toolbox as additional interface blocks are required to connect to simulation elements from the Simscape Toolbox. Although the Simscape Power Systems offers better models for the ultracapacitor and Li-ion battery components, the additional interface blocks add unnecessary complexity to the complete simulation model. Therefore, to investigate the practical behavior of the ultrafast energy capture and high electrical energy density storage subsystem along with the complete PMAD system, a simulation model was constructed in Matlab using the Simulink Simscape Electronics Toolbox.

Ultracapacitor Simulation Model for Simscape Electronics

The challenge with using the Simulink Simscape Electronics Toolbox is its lack of a behavioral model for ultracapacitors. A regular capacitor model could be used instead, but the fidelity of the system model is reduced. A solution was found to this challenge by modifying the supercapacitor model from the Simscape Power Systems Toolbox. The modification consisted of replacing the exterior interface elements from the Power Systems

Toolbox (see Figure 66, left image) with interface elements from the Simscape Electronics

Toolbox; the modifications are illustrated in Figure 66, right image. The modifications to the ultracapacitor model Simscape Power Systems allows for its use in the Simscape

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Electronics simulation environment; the parameters for the modified ultracapacitor model are shown in Figure 67. One of the negative effect of modifying the part lead to disabling the self-discharge feature of the model. Another caveat was to include the PowerGUI™, which allows the user to select the methods to solve a given circuit.

Figure 66: Modifications to the Ultracapacitor Model for Use with Simscape Electronics

Figure 67: Ultracapacitor Model for Simscape Electronics – Parameters and Options

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5.3.2 Modeling and Simulation Results

The general approach for incorporating the ultrafast energy capture and high electrical energy density storage system is detailed in Section 4.2.1. The implementation of this hybrid energy storage system requires additional power processing electronics in order to control the flow of intermittent electrical energy from the VMJ photovoltaic cells to the propulsion system.

The potential hardware implementation of the ultrafast energy capture and high electrical energy density storage system on-board the MUAV consists of using two DC-to-

DC converters in order to transfer the intermittent pulses of electrical energy form the VMJ photovoltaic cells to the propulsion subsystem. As illustrated in Figure 68, a front-end DC- to-DC converter is used to provide power regulation from the VMJ photovoltaic cells to the ultracapacitor bank; this DC-to-DC converter is also used to transfer the intermittent pulses of electrical energy from the VMJ photovoltaic cells to the ultracapacitor at rapid rates. Once the electrical energy is stored in the ultracapacitor bank, a second DC-to-DC converter is used to extract the electrical energy from the ultracapacitor bank and provide regulated power to the Li-Polymer battery pack in order to re-charge the battery pack on- board the MUAV.

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Ultrafast Energy Capture and High Electrical Energy Desnsity Storage System

Intermittent Energy + DC/DC Converter DC/DC Converter UC Bank Load High Energy Conversion (Ultracapacitor (Battery Charger) Li-Ion Laser Pulses (HILPB Receiver) - Charger)

Figure 68: Implementation of the Ultrafast Energy Capture and High Energy Density

Storage System for HILPB Applications from Figure 37

The benefit of this approach is that the front-end DC-to-DC converter allows the voltage produces by the VMJ photovoltaic cells to vary significantly while providing a stiff regulated power interface for the ultracapacitor bank. The negative impact of this approach, however, is increased system complexity and increased weight for the power system. To fully investigate this potential hardware implementation approach, a simulation model was constructed based on the block diagram from Figure 68; the simulation model of this ultrafast energy capture and high electrical energy density storage system is illustrated in Figure 69.

As illustrated in Figure 69, two DC-to-DC converters are used to control the energy flow from the HILPB power receiver to the propulsion subsystem. The HILPB power receiver was modeled using a controlled voltage source. A current limit is used after the first DC-to-DC converter to control the current flow into the ultracapacitor bank; the current limit was placed at the output of the DC-to-DC converter as this would more naturally represent a DC-DC switched converter with current limit capabilities (the voltage drop would happen at the output). A protection circuit is implemented following the 2nd

DC-to-DC converter to prevent over-discharging of the ultracapacitor bank; the

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ultracapacitor low charge protection circuit is shown in Figure 70. In order to control the amount of current flowing into the battery, a current limit block is utilized after the 2nd DC- to-DC converter. To simulate the propulsion subsystem, a constant current sink is implemented in the simulation model. The electrical energy produced by the VMJ photovoltaic cells from the transmitted laser beam is modeled as a controlled voltage source. The battery was modeled based on the requirement defined in Section 5.1.

Figure 69: Simulation Model of the Ultrafast Energy Capture and High Energy Density

Storage System Utilizing 2xDC/DC Converters

Figure 70: Ultracapacitor Low Discharge Protection Circuit

To simulate the model illustrated in Figure 69, the input source was set based on the hardware results obtained with the HILPB power receiver discussed in Section 4.3.

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Recall that the receiver was composed of nine VMJ cells in parallel, which produced an electrical output of 2000 mA-hour at approximately 20 Vdc. To simulate these results, the input voltage source for the model in Figure 69 was set to a constant 20 Vdc. The current limit at the output of the input DC-to-DC converter was set to 2 Adc to match the hardware results discussed in Section 4.3.

To simulate the intermittent laser pulses, the DC-to-DC converter block was switched on/off using the model’s input “fault” port. The parameters of the ultracapacitor bank were set based on the optimization results from Section 5.2.4. To save weight, the mass constraint for the ultracapacitor bank was selected at 1 kg. The GA optimization results from Table XII yielded an ultracapacitor bank with 10 ultracapacitor in series, where the ultracapacitor of choice would be FastCap’s EEx3V-450.

Simulation results illustrating the incorporation of the ultrafast energy capture and high energy storage system into the PMAD system on-board the MUAV are illustrated in

Figure 71 and Figure 72. The goal of this simulation was to demonstrate the capability of the ultracapacitor bank to capture the intermittent laser pulses and for the ultracapacitor bank to trickle-charge the battery. As demonstrated by the simulation results in Figure 71, the objective of this simulation model was successfully accomplished. While these simulation results focused on demonstrating the fundamental capability of the ultrafast energy capture and high energy storage system, Section 5.5 optimizes the entire system for maximum end-to-end energy transfer efficiency based on a various flight scenarios.

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Figure 71: Simulation Results of the Ultrafast Energy Capture and High Energy Density

Storage System Utilizing 2xDC/DC Converters – Input Energy Source and Ultracapacitor

Bank

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Figure 72: Simulation Results of the Ultrafast Energy Capture and High Energy Density

Storage System Utilizing 2xDC/DC Converters – Battery and Load

5.3.3 Intermittent Optical Energy Transmission: Duty Cycle Optimization

The purpose of the ultrafast energy capture and high electrical energy density storage subsystem is to enable energy transfer to the MUAV via intermittent energy pulses rather than continuous tracking of the MUAV with the laser beam. In order to achieve maximum end-to-end power transfer efficiency, the duty cycle of the transmitted energy pulses to the MUAV must also be optimized. To optimize the duty cycle of the intermittent energy pulses, the Simulink Design Optimization™ (SDO) toolbox is used to define cost

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functions by creating design requirements for the signals of interest within the simulation model.

The SDO toolbox allows for automatic tuning of the model parameters to meet user-defined time-domain or frequency-domain requirements. A variety of optimization algorithms may be used with the SDO, including the global optimization algorithm known as pattern search. The optimization requirements are added to the simulation model by selecting the signal to be optimized and imposing constraints on this signal such as amplitude bounds and other specific signal constraints (maximum and minimum) along with various signal properties including signal final value, signal mean value, etc.

The Simulink model depicted in Figure 69 was modified to incorporate the SDO as means of optimizing the complete system; the modified simulation model is shown in

Figure 73. The GA optimization results from Section 5.2.4 were also incorporated into the

Simulink model; specifically, the parameters associated with the ultracapacitor bank. The

SDO response optimization tool was configured to optimize the model response by evaluating multiple cost functions at the same time. An SDO cost function is defined as a signal requirement for any of the desired signals available in the Simulink model. In order to define variables as optimization cost functions, these variables were first defined as visible signals in the Simulink model as shown in Figure 74.

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Figure 73: Simulation Model of the Ultrafast Energy Capture and High Energy Density

Storage System for HILPB Applications Configured for the SDO

Figure 74: Optimization Requirements – Converting Design Variables into Signals

A power consumption profile was constructed and added to the simulation model.

The power consumption profile for the RQ-11B Raven was constructed based on a typical mission profile. As detailed in Section 5.1, a typical mission profile for the RQ-11B Raven starts with the MUAV climbing for approximately 20 seconds to reach an operational altitude of 300-500 ft. This altitude climb is characterized by setting the throttle to 100% for 20 seconds; the 100% throttle point corresponds to 6 Adc as shown in Table X. Once the MUAV reached its operational altitude, the autopilot mode is enabled. This normal mode of operation is characterized by setting the throttle to 55%, which corresponds to an

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amperage draw from the battery pack of 1.22 Adc. This mission profile was simulated in

Matlab Simulink via a current-controlled current-source, which is controlled by a signal that mimics the MUAV mission profile; the Simulink implementation of the MUAV mission profile is illustrated in Figure 75.

Figure 75: Mission Profile Implementation for the RQ-11B Raven

Objective Function Definition using SDO

For the HILPB application, the goal is to optimize the duty cycle of the incoming pulsed optical energy. The intermittent laser pulses are simulated with a pulse generator block as shown in Figure 76; the pulses were delayed by 7200 seconds to start after the Li- ion battery is discharged, i.e. one complete typical mission of the RQ-11B Raven MUAV.

Two SDO cost functions were formulated based on the variables within the pulse generator model by maximizing the “pulsePeriod” design variable and minimizing the “pulseWidth” design variable. The constraints of these two cost functions were based on the battery

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voltage: a signal bound was created for the battery voltage signal, to ensure that the battery voltage does not decrease below its low charge state of 21.9 Vdc.

Figure 76: Duty Cycle Optimization of Intermitted Laser Beam – Objective Function

Definition

Simulation Results using the SDO Toolbox

Once the SDO cost functions and its constraints were defined and implemented, the

Simulink model shown in Figure 73 was optimized. The optimization method selected was the gradient descent (fmincon) method, which makes use of the sequential quadratic programming algorithm. The initial conditions for the “pulsePeriod” and the

“pulseWidth” design variables were set as shown in Figure 77. The simulation was set to run for a duration to mimic 200% the normal mission profile of the RQ-11B Raven MUAV.

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The SDO simulation results and the SDO optimization progress report are illustrated in

Figure 78 and Figure 79, respectively.

Figure 77: Initial Conditions and Signal Requirements Settings for the Simulink Design

Optimization

Figure 78: SDO Simulation Results with the Gradient Descent Method

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Figure 79: SDO Simulation Results – Optimization Progress Report

The SDO simulation results depicted in Figure 78 and Figure 79 found an optimal duty cycle for the laser beam of 57.77% with a pulse duration of 3600 seconds. Using the

HILPB power receiver detailed in Section 4.3, a laser pulse duration of 2052 seconds is required to re-fuel the MUAV for indefinite operation at an altitude of 300-500 ft and while the MUAV operates on autopilot. The system simulation results of the ultrafast energy capture and high energy density storage system on-board the MUAV using the optimum duty cycle determined by the SDO are illustrated in Figure 80 and Figure 81. These simulation results indicate that the limitation of the system is due to the current limit of 2

A used to charge the ultracapacitor bank; recall that the 2 A limit was used to mimic the

HILPB power receiver that was integrated into the MUAV and the hardware results as detailed in Section 4.3. In order to decrease the duty cycle of the directed optical energy,

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the design of the ultrafast energy capture and high energy density system depicted in Figure

68 must be further optimized; hence, the system-level optimization is outlined in Section

5.4.

Figure 80: Simulation Results with the SDO’s Optimum Duty Cycle – Input Energy

Source and Ultracapacitor Bank

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Figure 81: Simulation Results with the SDO’s Optimum Duty Cycle – Battery and Load

5.4 System Optimization for Maximum End-to-End Power Transfer Efficiency

The energy storage elements that make up the front-end of the ultrafast energy capture and high electrical energy density storage subsystem, which are used to capture the intermittent energy pulses, were optimized using the GA optimization routine as detailed in Section 5.2. For HILPB applications, however, in addition to optimizing the front-end energy storage elements, it is necessary to optimize the complete system and its components in order to achieve maximum end-to-end power transfer efficiency.

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5.4.1 System Design Optimization

The simulation results detailed in Section 5.5.1 define a duty cycle for the directed optical energy of 57.77% with a pulse duration of 3600 seconds. To improve (reduce) the duty cycle of the directed optical energy, further system design optimization is required of the ultrafast energy capture and high electrical energy density storage system detailed in

Section 5.4.2. First, the input current limit of 2 Adc can be eliminated by re-designing the

HILPB power receiver to include additional VMJ photovoltaic cells. Another modification, consists of using a single DC-to-DC converter instead of two DC-to-DC converters to transfer the intermittent pulses of electrical energy form the VMJ photovoltaic cells to the propulsion subsystem. A block diagram of the modified system is illustrated in Figure 82.

For the proposed implementation depicted in Figure 82, the bus voltage produced by the HILPB receiver must match the voltage of the ultracapacitor bank. There are two options available to accomplish this, i.e. to match the voltage of the HILPB receiver with the voltage of the ultracapacitor bank:

a) Increase the voltage stack of the ultracapacitor bank by adding additional series

connected ultracapacitors

b) Design a HILPB receiver to produce a voltage output equal to the ultracapacitor

bank

For option “a”, adding series connected ultracapacitors to the energy storage system will increase the weight of the system. Option “b”, however, provides a feasible solution because of the inherit advantage in the design of the VMJ photovoltaic cells. As illustrated

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in Figure 82, the second option makes use of the inherit advantage in the design and construction of the VMJ photovoltaic cells. As explained in Section 2.2.1, the series- connection of the silicon junctions within a VMJ cell allows the designer to add as many silicon junctions as desired in order to match the desired bus voltage of the load. Additional

VMJ cells may be added to match the amperage requirement of the load. If the voltage produced by the VMJ photovoltaic cells is matched with the maximum voltage of the ultracapacitor stack, there is no need for a front-end DC-to-DC converter. Eliminating the front-end DC-to-DC converter reduces the weight of the MUAV and the complexity of the hybrid energy storage system. The experimental demonstration of the HILPB technology, which is detailed in Section 2.2, used a HILPB power receiver built using 40-junction VMJ photovoltaic cells, where each individual VMJ cell produced 20 Vdc. The HILPB power receiver can incorporate multiple VMJ photovoltaic cells for increased amperage capability.

Figure 82: Hybrid ESS for HILPB Applications – Option #2 (One DC/DC Converter

Used for the Transfer of Electrical Energy On-Board the MUAV)

To fully investigate the new ultrafast energy capture and high electrical energy density storage system, a simulation model was constructed based on the block diagram in

Figure 82. The new solution requires a single DC-to-DC converter instead of two DC-to-

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DC converters to transfer the intermittent pulses of electrical energy form the VMJ photovoltaic cells to the propulsion subsystem. The simulation model of this PMAD subsystem is illustrated in Figure 83. The HILPB power receiver was modeled using a controlled voltage source, which was powered on/off to simulate the intermittent laser pulses.

Figure 83: Simulation Model of the Modified Ultrafast Energy Capture and High Energy

Density Storage System for HILPB Applications Configured for the SDO

5.4.2 Genetic Algorithm Optimization of the Energy Capture Elements

The new ultrafast energy capture and high electrical energy density storage system depicted in Figure 83 does not include the front-end power processing electronics. As explained in Section 5.4.2, there are two implementation options available that serve as possible solutions: manufacture new VMJ cells or use exiting VMJ cells and optimize the

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energy capture elements of the hybrid ESS. The first option of manufacturing new VMJ cells may be pursued by customers interested in bulk manufacturing to decrease cost. For research purposes, however, the existing VMJ photovoltaic cells were considered for use in this research and thus for the modified ultrafast energy capture and high electrical energy density storage system depicted in Figure 83. As detailed in Section 2.2.1, the maximum open voltage of VMJ photovoltaic cells is 25 Vdc. Since the voltage of the VMJ photovoltaic cells must match the voltage of the ultracapacitor bank, a new ultracapacitor bank was designed and optimized with the new requirements. To this end, the ultracapacitor bank was designed and optimized using the GA optimization routine detailed in Section 5.2. The new bus voltage of 25 Vdc was used to optimize the energy capture elements of the hybrid ESS using the user-interactive GA routine detailed in Section 5.2.

Therefore, the optimization routine was set-up as follows:

 Discharge ratio (%): minimum of 20 % and maximum of 80 %

 Maximum discharge current from the ultracapacitor bank: 3 Adc

 Maximum allowable mass, i.e. weight constraint (kg): 1 kg

 Maximum number of ultracapacitors in series: 8

 Maximum number of series ultracapacitors in parallel: 3

The mass constrained of 1 kg was entered in the Matlab Command Window. The GA optimization results are shown in Figure 84 and Figure 85. From the database of available ultracapacitors depicted in Table XI, the GA optimizer results indicate that line item #5 was the optimal ultracapacitor for this application. Line item #5 from the database in Table

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XI is an ultracapacitor manufactured by Maxwell with part number BCAP0350-E270-T11 and the following specifications:

 Voltage: 2.70 Vdc

 Capacitance: 350 F

 Mass: 60 g (0.06 kg)

 ESR: 3.2 mΩ (0.0032 Ω)

Furthermore, the GA optimizer results indicate that the front-end of the new ultrafast energy capture and high electrical energy density storage system depicted in Figure 83 is to be composed of two parallel strings with eight ultracapacitors in each string. Eight ultracapacitors in series yields a maximum stack voltage for the ultracapacitor bank of 21.6

Vdc. Even though the open voltage of the VMJ photovoltaic cells is 25 Vdc, the ultracapacitor bank will not be overcharged because the under-load voltage of VMJ cells is typically 20 Vdc, which is less than the maximum ultracapacitor stack voltage of 21.6

Vdc. For simulation purposes, the laser pulses are simulated with a controlled-voltage source that outputs 20 Vdc to reflect the under-load condition of the HILPB power receiver.

The simulation model of ultrafast energy capture and high electrical energy density storage system illustrated in Figure 83 was updated to reflect the optimized ultracapacitor bank.

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Figure 84: GA Optimization Results – Optimization Progression

Figure 85: GA Optimization Results – Matlab Command Window

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5.4.3 System Response Optimization

The simulation model for the new ultrafast energy capture and high electrical energy density storage system was updated as illustrated in Figure 83. For maximum end- to-end power transfer efficiency, the duty cycle of the transmitted energy pulses to the

MUAV must be optimized. Therefore, Simulink’s SDO toolbox is implemented to optimize the duty cycle of the intermittent energy pulses.

The SDO response optimization tool was configured to optimize the model response by evaluating multiple cost functions at the same time. The SDO cost functions were defined as model requirements for the signal behavior of interest. The SDO cost functions and search variables were defined as visible signals in the Simulink model as shown in Figure 74.

One of the optimization objectives is to determine the minimum duty cycle of the pulse train of intermittent energy pulses. To achieve this objective, two cost functions are defined using the variables from the Simulink block used to generate the pulse train of intermittent energy pulses, i.e. to maximize the design variable “pulsePeriod” and to minimize the design variable “pulseWidth”.

The second cost function is based on the primary function of the ultrafast energy capture and high electrical energy density storage system depicted in Figure 83, which is to capture high energy pulses from an optical energy source. This energy capture and storage system is capable of capturing energy pulses of up to 100 Adc. Hence, to further optimize the energy capture and storage system depicted in Figure 83, the input current limit was added as an additional optimization objective. Therefore, the cost function is

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defined as minimization of the Simulink constant “InputCurrentLmit” within the “Current

Limiter” block-model.

The time-domain constraint was defined based on the minimum battery voltage; a signal bound was created to ensure that the battery voltage does not reach its low state of charge of 21.9 Vdc. In summary, the SDO response optimization tool allowed for minimization of the pulse width and input current limit design variables, maximization of the pulse period design variable, while satisfying time-domain constraints on the battery voltage. The design variables and their initial conditions are depicted in Figure 86; the optimization cost functions are illustrated in Figure 87.

The optimization results are shown in Figure 89. During the optimization process, the SDO optimization tool updates the plots for each design requirement. The optimization converged on seven iterations as depicted in the optimization report in Figure 90. The maximum period of the pulse was found to be 3600 seconds and the minimum pulse width was 16.30 %. Hence, the optimal duty cycle of duty cycle for the pulse train of intermittent energy pulses was found at 586 seconds or 9.7 minutes. The minimum input current was found to be 11.21 Adc. From an operations perspective, the ultrafast energy capture and high electrical energy density storage system allows the MUAV to fly perpetually if it receives 11 Adc for 10 minutes in one hour.

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Figure 86: Design Variables with Initial Conditions

Figure 87: Optimization Cost Functions

Figure 88: SDO Response Optimization Method and Options

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Figure 89: System Design Optimization Results

Figure 90: System Design Optimization Results – Optimization Progress Report

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Figure 91: Simulation Results 1xDC/DC Converter and SDO’s Optimum Duty Cycle and

Input Current Limit – Input Energy Source and Ultracapacitor Bank

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Figure 92: Simulation Results 1xDC/DC Converter and SDO’s Optimum Duty Cycle and

Input Current Limit – Battery and Load

5.4.4 Sensitivity Analysis

A sensitivity analysis was performed on the simulation model depicted in Figure

83 to evaluate and understand how the design variables influence the optimization cost functions for the signals of interest defined in the above section. In general, sensitivity analysis is defined as “the study of how uncertainty in the output of a model (numerical or otherwise) can be apportioned to different sources of uncertainty in the model input” [120].

In the case of the ultrafast energy capture and high electrical energy density storage system

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illustrated in Figure 83, the sensitivity analysis identifies which design variables (input current limit, pulse width, and pulse period, have the greatest impact on the model’s cost functions such as maintaining the battery voltage above 21.9 Vdc. In addition, sensitivity analysis provides an understanding of how variations in model parameters influences behavior of the model and the cost functions. This information can be used to guide the design process for a potential hardware implementation and to increase performance, reliability, and robustness of the Simulink model or for the final hardware product.

The SDO Sensitivity Analysis tool, which is part of the Simulink Design

Optimization Toolbox, was implemented to perform a global sensitivity analysis of the ultrafast energy capture and high electrical energy density storage system illustrated in

Figure 83, in order to understand, analyze, and explore the optimization problem and the model’s design space using various statistical techniques. To use the SDO Sensitivity

Analysis tool, the first step was to identify the parameters that impact the model’s behavior and the cost functions. Hence, the design variables along with their initial conditions and the optimization cost functions depicted in Figure 86 and Figure 87, respectively, were imported directly from the SDO Response Optimization as shown in Figure 93.

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Figure 93: Exporting Optimization Cost Functions and Design Variables from the SDO

Response Optimization to the SDO Sensitivity Analysis

The next step was to create a large number of samples that represents the design space for the model, where the design space is a set of all possible values that its search variables can assume. A randomly generated sample space was created for the following design variables: pulse width, pulse period, and input current limit. As depicted in Figure

94, the sample space for each parameter has 100 randomly generated samples with uniform probability distribution; in other words, all 100 samples are equally likely to be available.

To visually inspect that each sample set convers the entire design space, the sample set for each parameter is displayed as a scatter plotted in Figure 95. The bar graphs in Figure 95 are histograms, which show how the samples for each parameter are distributed.

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Figure 94: Sample Design Space Generation for Each Parameter

Figure 95: Visualization of the Sample Design Space for Each Parameter

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Recall that the optimization cost functions for the ultrafast energy capture and high electrical energy density storage system illustrated in Figure 83, were imported directly from the SDO Response Optimization as depicted in Figure 93. Once the sample set and requirements have been defined, the model in Figure 83 was evaluated for all parameter samples to determine which parameters exert the greatest influence on the model’s cost functions. Hence, to analyze the relationship between the parameter variations and the cost function values, the model was simulated automatically using each row in the parameter sample set as an input while simultaneously calculating the maximum pulse period, minimum pulse width, minimum input current limit, and the battery voltage.

The sensitivity analysis was performed visually and statistically. The evaluation results are displayed in Figure 96, where each cost function is plotted against all design variables. The histograms displaying the distribution for each cost functions are shown on the right of Figure 96; the contour plots of the evaluation results are displayed in Figure

97. The cost function for the battery voltage displays a trend and a dependency of convergence to the 21.9 Vdc bound with high values of pulse period, low values of pulse width, and high values of input current limit. There are no trends or dependencies for the other cost functions with respect to mutually exclusive variables. The evaluation results are further analyzed statistically to determine which parameters have the greatest influence on behavior by using the following statistics techniques: correlation, standard regression, and partial correlation. A tornado plot was generated where the parameters are ranked based on their influence. From the tornado plot shown in Figure 98, one can see that the battery voltage is directly proportional to the pulse period and inversely proportional to the pulse width and the input current limit. Furthermore, the pulse width does not exert much

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influence on the battery voltage; in contrast, the input current limit and the pulse width do influence the battery voltage.

Figure 96: Sensitivity Analysis Evaluation Results – Cost Function Distribution for Each

Design Variable

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Figure 97: Sensitivity Analysis – Contour Plots of Evaluation Results

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Figure 98: Sensitivity Analysis – Statistics Evaluation Methods

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CHAPTER VI

TECHNOLOGY INFUSION AND APPLICATIONS

The ultrafast energy capture and high electrical energy density storage system is generalized for other high-power commercial, industrial, and aerospace applications. The applications enabled by the ultrafast energy capture and high electrical energy density storage system are presented; the rationale and benefits of using the generalized hybrid energy storage system are also discussed.

6.1 Generalization and Scalability to other Applications

The ultrafast energy capture and high electrical energy density storage system has been developed and optimized in this dissertation to enable the AFRL program “Airborne,

Integrated Surveillance and Close Operations Support System”, with the goal of ‘refueling’ a fleet of all-electric MUAVs in-flight, in order to provide a 24/7 aerial dominance of the theater of operations. While solving one of the needs for this specific application led to the development of the ultrafast supply/extended energy storage system, there are other applications which could make use of this energy storage system. There is a real need and

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urgency in these areas to rapid charge a high energy density storage system. Therefore, the ultrafast supply/extended energy storage system can be generalized for other applications such as high-power commercial, industrial, and aerospace applications with specific examples that include manufacturing, commercial aircraft, space-crafts, and electric vehicles; a list of potential applications is detailed in Table XIII.

TABLE XIII: SUMMARY OF POTENTIAL APPLICATIONS

The majority of applications depicted in Table XIII are based on using the HILPB technology or other optical and photonic energy sources. It follows that the ultrafast energy capture and high electrical energy density storage system can be generalized based on the available source of energy type as shown in Figure 99.

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Figure 99: Configurations of the ultrafast energy capture and high electrical energy

density storage system for Optical, Electrical, and Magnetic Energy Sources

6.2 Civilian Space Applications

The ultrafast supply/extended energy storage system developed in this dissertation may be used in a number of civilian space applications that make use of wireless power transmission. The use of lasers to transmit power for civilian space applications comprises of the following three categories: laser power beaming from ground to space, laser power beaming from space to Earth, and laser power beaming from space to other space assets such as cross-linking or downlinking to surface assets such as cross-linking or downlinking to surface assets. Laser power beaming from a ground site to space assets include

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the following applications: orbit transfer of communication satellites, supplementary power to orbiting communication satellites, rescue missions of certain failed satellites, supplementary power to space station, on orbit high power laser applications, illumination of natural or manmade objects out to lunar orbit, power to a lunar base during the 14 day lunar night, clearing space debris, and manned missions to Mars [121]. However, only applications that utilize photovoltaic arrays to receive the laser power can use the ultrafast supply/extended energy storage system. Therefore, the civilian space applications viable for this energy system include: satellites during eclipse, resurrection of satellites failing due to solar array degradation, orbital transfer of spacecraft, and night power to a lunar base [122]. Furthermore, the ultrafast supply/extended energy storage system enables the use of optical communication and intermittent power transfer via a single channel/system of intermittent beamed laser power.

6.2.1 Supplemental Power for Satellites

There are two applications that involve providing supplemental power for satellites operating in the Geosynchronous Earth orbit (GEO) and the low Earth orbit (LEO), which could make use of the ultrafast supply/extended energy storage system: providing power during the sun eclipse and providing power for power system failure due to radiation- degraded arrays or internal battery failure.

All satellites operating in GEO and LEO are powered by photovoltaic arrays.

Satellites operating in GEO, around Earth’s equinoxes, experience an eclipse of the Sun once per day with a duration of approximately 70 minutes, for a total of 90 days in one

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calendar year. Satellites operating in LEO have 5500 Sun eclipses in one year. During the

Sun eclipse, the satellites are powered by an on-board battery, which is charged by the satellite’s photovoltaic arrays. While the battery plays a critical role in the operation of the satellite, the downside is its weight, which is 42% of the power system’s total mass, including the photovoltaic arrays (the power system is approximately 1/5 of the satellite’s total mas) [123]. The second application for supplemental power to satellites, consists of providing power to the satellite when the power system reached its end of life due to solar array degradation or due to an internal battery failure [124].

The solution for both applications, consists of eliminating the energy storage system and beaming optical energy to the satellite with a high power laser from a ground location as depicted in Figure 100. The disadvantage, however, is the need to continuously track the satellite with a high-power laser beam. In the case of the Sun eclipse, a GEO satellite must be tracked continuously during the entire duration of the eclipse for 70 minutes. The ultrafast supply/extended energy storage system would provide an elegant solution as it would reduce the mass of the energy storage subsystem and improve the reliability of the battery by decreasing its cycles. Most importantly, however, the ultrafast supply/extended energy storage system would eliminate the need to continuously track the satellites with a high intensity laser for long periods of time.

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Figure 100: Extending Battery and Satellite Life via Intermittent HILPB [124]

In 2011, NASA created the Technology Applications Assessment Team (TAAT) to identify promising technologies, which could be used in future space exploration applications. A total of six technologies were identified that could be demonstrated by ground and space-flight tests. One of the six identified technologies that could be demonstrated with existing launch vehicles (existing assets developed for the Space Shuttle and the Constellation programs) was laser power beaming from space assets to other space assets and from Earth to space assets. The laser power beaming demonstration proposal would consist of installing a laser system on-board the International Space Station (ISS) to beam power to one of United States Air Force Academy’s FalconSATs. The test objective was to beam 300 W of electrical power from ISS to the FalconSAT, when the satellite was within ISS’ 500 km range; the window of opportunity to beam power was calculated to be approximately 30 seconds. The success criteria was defined by the ability to use the received beam energy for the satellite’s propulsion system, i.e. to propel the satellite [125].

The 30 second window of opportunity to beam power to the satellite, presents a technical challenge in this endeavor as the current state-of-the-art energy storage system on-board satellites cannot absorb the beamed energy within 30 seconds. Therefore, the ultrafast

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supply/extended energy storage system developed in this dissertation would represent a viable solution to this technical challenge by its ability to absorb large amounts of energy in short durations.

Figure 101: NASA Proposed Laser Power Beaming Demo – ISS to FalconSATs [125]

6.2.2 Power for Lunar and Deep Space Exploration Assets

The ultrafast supply/extended energy storage system developed in this dissertation could also be used as the primary or auxiliary energy storage system for lunar assets such as a lunar base or a lunar rover. One of NASA’s visions for space exploration is to use the

Moon as a test-bed to evaluate technologies needed to explore the plant Mars and beyond.

This test-bed program on the Moon will consist of robotic rovers and eventually a permanent human outpost [126]. The lunar base and robotic rovers require electrical power for nominal operation. Hence, providing power to these lunar assets is a critical component to achieve mission success.

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Figure 102: Lunar Assets (credit: Anna Nesterova; Bryan Versteeg, spacehabs.com)

Generating electrical power for lunar assets can be accomplished by implementing either a solar power source or a nuclear power source. Due to the risks associated with using nuclear power, the solar power generation source is an attractive option. However, one of the challenges associated with solar-based power generation system is the lack of sunlight during the 354-hour lunar night. In order to provide power during this time, electrical energy could be stored in batteries. It is estimated that approximately 100 kW and 50 kW of electrical power is required during the lunar day and the lunar night, respectively. In order to store this electrical power, the mass of the battery pack is estimated to exceed one million kilograms [127]. It follows that the energy storage system is a critical component of a lunar base due to the cost associated with transporting such heavy mass to the Moon. Therefore, the primary criteria for designing an energy storage

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system for a lunar base is its specific power of the energy storage system measured in watt- hours per kilogram (W-hr / kg) [128].

The weight of the energy storage system required to operate a lunar base during the

354-hour lunar night is cost prohibitive to transport it from Earth to Moon. One solution is to complement the solar power generation by beaming power with a laser from satellites placed in the low lunar orbit (LLO). Since the LLO is approximately 100 km, the orbital period is approximately four hours and a minimum of three satellites would be required to beam power continuously to the outpost during the lunar night. The ultrafast supply/extended energy storage system proposed in this dissertation would eliminate the need of beaming power continuously and thus reduce the number of satellites needed for power beaming. Furthermore, the ultrafast supply/extended energy storage system may reduce the mass of the classic energy storage system by reducing the number of batteries.

The ultrafast supply/extended energy storage system can be scaled down for lunar robotic applications such as lunar rovers that could be used to explore the polar regions of the moon or moon craters that are not illuminated. Satellites placed in LLO could beam optical energy intermittently to the rovers allowing them to explore landscape that is not illuminated for longer durations. The same concept can be used for the exploration of caverns on Mars using solar rovers designed with the ultrafast supply/extended energy storage system, where laser power can be beamed intermittently. Lastly, the ultrafast supply/extended energy storage system can also be used for other deep space exploration missions to power assets in the Lunar, Jovian, and other orbits for deep space planets

(Venus, etc.) where solar illumination is not available.

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6.3 Department of Defense (DoD) Applications

The ultrafast supply/extended energy storage system developed in this dissertation may enable a number of DoD space and terrestrial applications. The DoD space applications are based on WPT, specifically laser power beaming from space to other space platforms and from space to Earth platforms. Space-to-space laser power beaming includes applications such as the System F6 and the Phoenix programs sponsored by the Pentagon’s

Defense Advanced Research Projects Agency (DARPA). The space to Earth applications are based on using a space-based solar power (SBSP) system to beam power to a multitude of platforms on Earth.

6.3.1 DoD Space Applications

Modular Satellite Architecture

From 2007 to 2013, DARPA had invested over $200 million in the Future, Fast,

Flexible, Fractionated, and Free-Flying Spacecraft United by Information Exchange also known as the System F6 program [129]. The goal of this program was to demonstrate the benefits of a new fractionated satellite architecture operating in a space experiment by improving the system’s adaptability and survivability. The new satellite architecture was set to replace the traditional spacecraft architecture, which was designed to operate with multiple functionalities, with a cluster of smaller satellites that would share resources and communicate wirelessly [130]. A pictorial illustration of the System F6 program is depicted in Figure 103, where one of the six primary functions is WPT. Integrating the

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ultrafast supply/extended energy storage system on-board each satellite would further enable the WPT function of the System F6 program by eliminating the need to track the satellites with a laser beam continuously; instead, intermittent energy pulses would be delivered to each satellite.

Figure 103: System F6 – Pictorial Illustration [131]

Figure 104: System F6 – Wireless Data & Power Transfer [129, 132]

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Space-based Solar Power

Space-based solar power is defined as collecting solar energy in space and transmitting it to platforms on Earth or to other space assets via microwave or laser power beaming. This concept was first proposed in 1968 by Peter Glaser in an effort to highlight the need for humanity to transition from fossil fuel and nuclear energy sources to solar- based energy in order to ensure its survival as a species [133]. A “fresh look” analysis of concepts for generating solar power in space to support terrestrial applications was performed by NASA in 1995, where it was concluded that the geosynchronous orbit would be the optimal orbit for a solar plant in space [134]. In 2006, several new concepts were proposed by Landis with the goal of making this concept practical and economically feasible [135]. The National Security Space Office emphasized the need to implement the solar-based power concept as means to solve global security and environmental challenges caused by declining natural resources and expanding human populations [136]. The space- based solar power represents an attractive solution to the growing global demand for energy and its direct environmental impact, because large solar arrays in the geosynchronous orbit can collect gigawatts of electrical energy, when can be beamed to Earth.

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Figure 105: Space-Based Solar Power – Energy Resource Opportunity [136]

The concept of beaming space-based power to Earth is gaining traction as the

European aerospace group EADS-Astrium is looking to operate a satellite that can beam

10 kW of electrical power to Earth, capable of running 10 homes [137]. The concept of

SBSP is illustrated in Figure 106; a video depicting SBSP and its application to supply electrical energy on Earth is available on-line at https://vimeo.com/30693126 [138].

Beaming power continuously for extended periods of time can be dangerous for birds and various aerial assets. The ultrafast supply/extended energy storage system enables the power delivery to be intermittent in nature depending on a window of opportunity for a clear line of sight. Therefore, for space-based solar power, the ultrafast supply/extended energy storage system enables intermittent power delivery to a variety of terrestrial and space platforms including: high altitude unmanned platforms and UAVs, naval platforms, and other space satellites.

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Figure 106: Space-Based Solar Power – Laser Power Beaming to Earth (credit: Graham

Murdoch, mmdi.co.uk). Used with permission, Appendix D.

6.3.2 DoD Terrestrial Applications

Forward Operating Base

A forward operating base (FOB) is a temporary military base composed of 50 to

5000 personnel and designed to support smaller tactical operation teams (reconnaissance or surveillance). Electrical power availability is a critical necessity for the FOB’s nominal operation. Generators that run on fossil fuel are used for lager FOBs to produce the

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required electrical energy [139]. Since these bases tend to operate in remote areas, resupply missions by air or ground are risky and costly. For example, in 2007 there were 170 human casualties during fuel resupply missions by ground vehicles in Iraq and Afghanistan [140].

Wireless power transfer via microwave or laser power beaming are being considered as alternative solutions to fossil fuel resupply missions. Due to the large antenna diameter, microwave power beaming is considered for large FOBs. Laser power beaming can be used for small or larger FOBs; however, continuous power beaming for extended periods of time is required in order to charge the on-base energy storage system.

The ultrafast supply/extended energy storage system can eliminate the need to beam high intensity optical energy continuously from a single source. Instead, intermittent high energy pulses can be beamed from multiple air or ground platforms.

Field Operations Teams

Field operations teams are made up of foot soldiers operating in the field during regular patrols or in reconnaissance and surveillance missions. The modern foot soldier carries batteries to power electronic equipment such as radios and other logistics and information devices. Due to these additional electronic loads, the battery packs make up

15% to 20% of a soldier’s 70-90 lbs pack. The additional weight has been identified as a major problem for the land warrior and there are a number of active programs that seek to reduce this excess weight. For example, DARPA’s program Energy Starved Electronics aims to reduce the power consumption of portable electronics [141].

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One solution is to implement the ultrafast supply/extended energy storage system, which can be quickly recharged from multiple platforms. This hybrid energy storage system allows the soldiers to receive intermittent electrical power from air or ground platforms via laser power beaming, which eliminates the burden of carrying multiple battery packs. Furthermore, by beaming power intermittently makes the field operations team less detectable by unfriendly forces.

High Altitude Unmanned Airships

There is increased interest and demand from the U.S. Military Services for improved communication and surveillance capabilities. One of the lessons learned from the wars in Iraq and Afghanistan was the need to improve the intra-unit communications.

The future forces of the U.S. Military will be more dispersed and will need to extend the range of communication. Commercial or military satellite communication (SATCOM) services are used by various branches of the U.S Military for secure communication. In order to meet the communication demands of future forces, additional SATCOMs will be needed. The problem, however, is that these communication systems are costly, so other cost-effective solutions are needed. High-altitude airships (HAAs) are being considered as alternative cost-effective solutions to SATCOMs since they can provide similar services as geostationary satellites such as constant viewing angle along with surveillance and communication services. HAAs are solar-powered and fly at an altitude of approximately

65,000 feet [142].

In addition to military applications, there are a number of civilian commercial applications such as monitoring the Earth for science and weather, observing maritime and

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aerial transportation systems, navigation, telecommunications, and broadcasting [143].

There are many DoD contractors from Europe the U.S. that are interested in building high altitude unmanned platforms. For example, Thales Alenia’s Space Division is building a

5 kW solar-powered HAA, named Stratobus (shown in Figure 107), which will be ready for testing in 2018. The field of view for the Stratobus is 500 km and its payload capability is 250 kg [144].

The power consumption requirements represent a major design issue for high altitude, long endurance, and platforms as some of the electrical loads include: electric motors used for propulsion, compressors, other electrical systems required for nominal operation, and the payload. Solar cells are mounted on top of HAAs to harvest the solar energy, which is used during the day; batteries supply the required energy during the night.

The photovoltaic arrays add unwanted weight to the HAA. Hence, the weight of the photovoltaic power plant is a major design tradeoff.

Beaming optical energy to the HAA from space-based solar plants or other high altitude platforms as depicted in Figure 107 is technologically feasible. However, tracking the HAA continuously for tens of minutes to charge the on-board batteries is not operationally practical. The ultrafast supply/extended energy storage system can be implemented on-board the HAA to allow the HAA to receive energy intermittently during day or night. The ability to receive power during the night from various platforms based on an intermittent energy signal of opportunity means that less energy is required to be stored on-board leading to a reduction in storage capacity requirements. In addition, to reducing the weight of the energy storage system, less photovoltaic cells would be needed and thus the weight of the solar plant is reduced too. High altitude platforms can be used

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as carries of MUAVs and can also be used to beam optical energy to MUAVs, HAAs, and various other terrestrial platforms.

Figure 107: High Altitude Airship – Stratobus (Courtesy of Thales Alenia Space)

Distributed Sensor Networks

Distributed sensor networks are used extensively in surveillance of military and civilian facilities as well as other assets of interest such as energy exploration fields. The primary limitations of these sensor systems is the availability of electrical power. Running dedicated power lines in support of these sensors is costly and risky. The cost and risk variables increase if the sensors are needed for temporary purposes only. Since some of these remote sensors operate from battery power, various energy harvesting technologies such as photovoltaic cells are used to re-charge the batteries. Beaming power to these sensors is being considered as means to reduce cost and risk of delivering electrical power.

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The on-board energy storage system of these sensors, however, becomes the limiting factor due to the time duration required to charge the sensor batteries.

Designing the sensors with the ultrafast supply/extended energy storage system would allow power to be beamed at intermittent intervals from a variety of platforms, thus further enabling the concept of delivering electrical energy to the sensors wirelessly. In addition, the ultrafast supply/extended energy storage system would allow for a reduced seize in the energy storage system implementation for wireless sensor systems. For military applications, another benefit in enabling power beaming from various platform would ensure the sensors are not detected by unfriendly forces.

Naval Applications

The U.S. Marine Corps and the US Navy have expressed interest in alternative power transmission where running power lines is not practical due to cost, risk, and terrain limitations. Ship to shore power delivery applications include providing power to sensors, small reconnaissance teams such as Navy Seals, and other seaborne platforms. With the recent progress in direct energy systems being implemented on-board ships, beaming power to these assets is a natural progression in using the directed energy systems. The ultrafast supply/extended energy storage system can be used on the platforms receiving the beamed energy. In the case of small reconnaissance team, the mass of the portable energy storage system is reduced by implementing the ultrafast supply/extended energy storage system, which would improve the mobility of the team. In addition to reducing the weight needed to carry, the intermittent nature of re-charging the energy storage system via a high- intensity energy signal of opportunity, the reconnaissance team would also avoid detection

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by unfriendly forces. The ultrafast supply/extended energy storage system may also be implemented on-board seaborne platforms, in shore-to-ship applications.

6.4 Commercial Terrestrial Applications

The ultrafast supply/extended energy storage system developed in this dissertation may be integrated into a variety of commercial terrestrial applications including: enabling new technology development such as hybrid-electric and turbo-electric aircraft; improving existing solar concentrators and rapid charge of electric vehicles; and enable future applications such as rapid charge of electric vehicles while in-motion using a pay-by- charge system.

6.4.1 Hybrid-Electric and Turbo-Electric Aircraft Applications

There is increased pressure on the aviation industry to develop future aircrafts that are quitter, use less fossil-fuel, produce less CO2 emissions, and are more efficient. For example, in 2011, the European Commission released a roadmap and vision for the

European aviation industry to be achieved by 2050. In order to protect the environment, this roadmap calls for a reduction in aircraft greenhouse gas emissions by 75% from the standards outlined in the year 2000. In addition, the roadmap also aims to reduce the aircraft noise levels by 65% [145]. To achieve these goals, the European aerospace industry led by Airbus, Air Bus Group Innovations, Siemens, and Rolls-Royce® are

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developing the eConcept, an architecture and configuration of a future hybrid-electric airliner, to be in operation in the year 2050.

Figure 108: eConcept – Hybrid-Electric Airliner (Courtesy of Airbus Group)

In support of eConcept, the Airbus Group Innovations and Rolls-Royce® are developing an electrical distributed hybrid-electric propulsion concept known as the E-

Thrust concept. E-Thrust is a serial hybrid propulsion system, where a single gas-powered turbine engine generates electricity, which is used to re-charge the battery bank and to power six electric fans, as illustrated in Figure 109. In this configuration, the gas-turbine along with the battery provide the power required by the aircraft during the take-off and climb phases. The batteries are re-charged by the gas-turbine engine when the aircraft is cruising and by the electric fans when they are wind-milling during the descent phase. The

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battery system will be sized for sufficient energy density to ensure safe take-off and landing of the aircraft in case the gas-turbine engine fails [146].

The ultrafast supply/extended energy storage system can be used as the energy storage system for the E-Thrust propulsion concept. During a typical aircraft flight pattern, there are instances when the electric turbo-fans are wind-milling intermittently due to the aircraft’s flight pattern or due to the wind effects and disturbances. The batteries cannot capture this intermittent excess energy. By incorporating the ultrafast supply/extended energy storage system, the intermittent excess energy from the electric turbo-fans can be captured by the ultracapacitor bank and transferred to the main battery system in a trickle- charge fashion. The ability to re-use excess energy from the electric turbo-fans, can reduce the overall size of the energy storage system used in support of E-Thrust, the serial hybrid propulsion system. In addition to this application, the ultrafast supply/extended energy storage system can be implemented in other in other advanced concepts for hybrid-electric and turbo-electric aircrafts looking to reduce the size of the energy storage system by recovering intermittent excess energy, transferring this energy to the primary battery energy storage system, which then re-uses the recovered energy for electric propulsion.

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Figure 109: E-Thrust – Serial Hybrid-Electrical Distributed Propulsion System [147]

(Courtesy of Airbus Group)

6.4.2 Rapid Charge Applications

The ultrafast supply/extended energy consumption system is an enabling technology for applications that require rapid charge; once potential application consists of charging electric vehicles at a faster rate. The Tesla Model 3, an all-electric vehicle manufactured by Tesla Motors, is configured with a single on-board battery charger, which re-charges the vehicle at a rate of 29 miles of range per hour of charge. Two chargers may be installed for an additional cost, which would increase the re-charge rate to 52 miles of range per hour of charge [148]. Tesla vehicles can also be charged at public Supercharger stations, where the specially equipped vehicles may be fully charged in 75 minutes [149].

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Hence, the time duration required to charge electric vehicles is still limited by the primary source for electric energy used for propulsion, i.e. the Li-ion battery technology.

To date, the energy storage system used for propulsion of electric vehicles is composed of Li-ion batteries. As detailed in Chapter 4, ultracapacitors are used in electric vehicles for regenerative braking / energy recovery, peak power assist, short-term back-up power, and vehicle starting operations. In these applications, however, the ultracapacitors are utilized as integrated modules made up of a number of ultracapacitors and are located in separate physical locations than the battery packs within the electric vehicle. With the recent advancement in ultracapacitor technology, the size of ultracapacitor cell is shrinking as FastCap Systems Co. has developed ruggedized and hermetically sealed AA-sized ultracapacitors [150], which are the same size as the battery cells used in the Tesla vehicles, i.e. Panasonic’s NCR 18650 lithium-ion AA battery cell. Therefore, for rapid charge of electric vehicles and other rapid charge applications, a new solution is presented in this dissertation: combine ultracapacitors and batteries at the cell level. This solution is outside the scope of this dissertation, so additional information are presented in Section 7.1 as future work.

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Figure 110: Battery Pack for Tesla Model S – Individual AA-Size Li-ion Battery Cells

Inductive Coupling

The ability to capture intermittent high energy pulses gives way to the concept of

‘refueling’ an electric vehicle using high-pulses of inductive energy. An energy lane within a multi-lane high-way can be build, where inductive energy generators can be placed at strategic distances. An electric vehicle may be re-charged while in motion by driving over the energy lane whenever the vehicle needs to re-fuel. The ultrafast energy capture and high electrical energy density storage system would allow the electric vehicle to capture and store the intermittent high energy pulses, and thus be able to re-charge quickly while in motion. A radio frequency (RF) identity tag may be added to the vehicle so that the driver can be billed automatically for the energy usage using a pay-by-charge system, thus

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eliminating the need to re-fuel overnight or at fuel stations, saving time and adding convenience. This concept can also be applied towards transit trains, and other related transportation systems and applications.

Solar Concentrators

Solar concentrators represent another area of applications where the ultrafast energy capture and high electrical energy density storage system may be used. Solar energy can be concentrated using mirrors or lenses into a small area, where a HILPB receiver can be used to convert the photonic energy into electrical energy. Multi kilo-watt solar concentrators have been built by Greenfield Solar Corporation [151]. The energy produced by these solar concentrators during the day can be stored in batteries and used during the night. The performance of these solar concentrator systems is limited by the availability of solar energy during cloudy days. The ultrafast energy capture and high electrical energy density storage system may be used in such solar concentrator systems to address the intermittent nature of solar energy availability by capturing the concentrated solar energy when it is available.

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CHAPTER VII

CONCLUSIONS AND FUTURE WORK

This dissertation presents the development and design optimization of an energy storage system used to advance the HILPB technology and enable a new realm of defense, civilian, and commercial applications. First, the ultrafast energy capture and high electrical energy density storage system is an enabling technology for the AFRL program “Airborne,

Integrated Surveillance and Close Operations Support System”, as it solves the practical limitation of tracking the all-electric MUAV for tens of minutes in order to re-charge its on-board batteries. Instead, simulation results demonstrated that intermittent high optical energy pulses are captured, stored, and transferred to the propulsion system by the

MUAV’s on-board ultrafast energy capture and high electrical energy density storage system, thus keeping the aircraft in-air indefinitely and providing a 24/7 aerial dominance of the theater of operations. Furthermore, the ultrafast energy capture and high electrical energy density storage system allows for long range optical re-fuelling of the MUAV from various platforms (airships, ground locations, satellites, and other far-away feasible support systems) based on the availability of an energy signal of opportunity that is of short duration.

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A power management and distribution system was designed, built, and tested to control the power flow from the HILPB receiver and distribute regulated power to the energy storage subsystem and to the aircraft’s propulsion subsystem. The development of the battery charging, communication, and control hardware was designed with the goal of a possible integration into the FQM-151A Pointer Aircraft.

The ultrafast energy capture and high energy density storage system was modeled, simulated, and optimized in order to be integrated into the MUAV for use in HILPB applications. To this end, the energy and power consumption requirements were researched and defined for the MUAV currently in-use by the U.S. Military. In addition, a typical mission profile was also defined based on flight test data used by the U.S. Military.

To meet the primary goal of the AFRL program, the intermittent pulses of optical energy beamed to the aircraft were minimized via the development of an optimization routine, which optimized the energy capture elements of the ultrafast energy capture and high energy density storage system; the objective function and constraints of this optimization routine were derived mathematically. Furthermore, this optimization routine was transformed into a design tool as it was used to select the appropriate ultracapacitor from a database of available products and to size the ultracapacitor bank, i.e. number of ultracapacitors in series and parallel; the optimal results were achieved using the genetic algorithm optimizer.

The energy and power requirements were used to construct a simulation model of the ultrafast energy capture and high electrical energy density storage system; the mission profile of the MUAV was used in various simulation scenarios. The simulation results demonstrated the following: the intermittent high-energy pulses are captured by the

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optimized ultracapacitor bank; once the energy is stored temporarily in the ultracapacitor bank, it can be transferred to the battery pack by trickle-charging the battery via a buck- boost DC-DC converter; and the duty cycle of the intermittent energy pulses transmitted to the MUAV can be optimized to achieve perpetual flight of the aircraft. The development of a simulation model, the simulation results, and the duty cycle optimization of the intermittent energy pulses transmitted to the MUAV are detailed in Section 5.3.

For the HILPB application, however, in addition to optimizing the front-end energy storage elements, it was necessary to optimize the complete system and its components in order to achieve maximum end-to-end power transfer efficiency. A new solution was developed, which requires one DC-to-DC converter instead of two DC-to-DC converters to transfer the intermittent pulses of electrical energy form the VMJ photovoltaic cells to the propulsion subsystem. The simulation model of this new PMAD subsystem was developed and optimized by defining and evaluating multiple cost functions and search variables simultaneously. A sensitivity analysis was also performed to evaluate and understand how the design variables influence the optimization cost functions for the signals of interest. The evaluation results were further analyzed statistically to determine which parameters have the greatest influence on behavior by using the following statistics techniques: correlation, standard regression, and partial correlation. It was determined that the battery voltage is directly proportional to the pulse period and inversely proportional to the pulse width and the input current limit. Furthermore, the pulse width does not exert much influence on the battery voltage; in contrast, the input current limit and the pulse width do influence the battery voltage.

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Lastly, the ultrafast energy capture and high electrical energy density storage system was generalized and scaled for use in other high-power DoD, civilian aerospace, and commercial applications. The rationale and benefits of using the generalized hybrid energy storage system for these applications was also presented.

In conclusion, the work presented in this dissertation clearly demonstrates the potential of the ultrafast energy capture and high electrical energy density storage system.

The weight and size of current ultracapacitor technology prohibits, for the present time, wide use of this energy storage system. However, the ultracapacitor technology is constantly improving as demonstrated by new start-up company FastCap Systems Co., which uses carbon nanotubes to develop ultracapacitors that have less weight and size than the ultracapacitors currently available on the market.

7.1 Future Work

The next step in meeting the objective of the AFRL program “Airborne, Integrated

Surveillance and Close Operations Support System”, is to modify the hardware prototype discussed in Section 4.3 in order to incorporate the ultrafast energy capture and high electrical energy density storage system. System-level integration of this power management and distribution into the MUAV could prove challenging, but it is a necessary next step. The last step requires a flight demonstration of the MUAV powered by intermittent high-intensity laser pulses.

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Another research topic consists of controlling the energy flow between ultracapacitors and Li-ion batteries using DC-to-DC converters. The ultracapacitor is a low impedance, high capacitive device. In contrast, when compared with the ultracapacitor, the Li-ion battery is a high impedance and low capacitance device.

Transferring energy from ultracapacitors to batteries and vice-versa in some cases, requires the use of current-fed DC-DC converters. Since energy transfer would involve large amperage peaks, further research is required to determine the optimal power stage and the control philosophy of these DC-DC converters.

Lastly, in support of the solution proposed for electric vehicles in Section 6.4.2, the modularity concept must be further explored. To this end, the optimal pairing combination of ultracapacitor cells with Li-ion battery cells must be researched. Once the optimal pairing is determined, a unidirectional or bi-directional DC-DC converter could be used to control the power flow. The pairing combination of ultracapacitor cells with battery cells coupled with the necessary power electronics for power flow control, can be packaged into one module. Larger energy storage systems can be built by connecting these building- block modules in parallel and series to accommodate for the desired voltage, function, and power rating of the energy storage system. The optimal control of the architecture such as distributed or centralized control can be further explored as the goal is to build a highly modular ultracapacitor and battery charge/discharge controller.

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APPENDICES

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APPENDIX A: OBJECTVE FUNCTION IMPLEMENTATION IN

MATLAB (MAIN RUN FILE)

Appendix A details the primary “.m” file that calls the objective function (see

Appendix B) and its constraints (see Appendix C) is outlined below in clear %% Definition of search variables % x(1) = Np (number of ultracapacitors in parallel) % x(2) = Ns (number of ultracapacitors in series) % x(3) = d_system (discharge ratio of the ultracapacitor system) % x(4) = i_system (discharge current of the ultracapacitor system) % x(5) = capacity, voltage, and ESR of available capacitors nvars = 5; % Number of variables massLimit = input('Please enter the mass limit for the ultracapacitor bank in kilograms = ');

%% Load the components' values for their respective voltage, capacitance, and ESR filename = 'UC Manufacturer Comparison 2016-07-05_Matlab_v2.xlsx'; sheet=1; capData = xlsread(filename,sheet,'C3:F17');

%% Bounds definition % Lower bounds % LB = zeros(4,1); LB(1) = 1; % Minimum number of ultracapacitors in parallel, Np = 1 LB(2) = 1; % Minimum number of ultracapacitors in series, Ns = 1 LB(3) = 20; % Minimum discharge ratio of the ultracapacitor bank, d_UCbank=40 LB(4) = 1; % Minimum discharge current of the ultracapacitor bank, i_UCbank=1 LB(5) = 1; % lowest index for capData

% Upper bounds % UB = inf(4,1); UB(1) = 3; % Maximum number of ultracapacitors in parallel, Np <= 3 UB(2) = 10; % Maximum number of ultracapacitors in series, Ns = 10 where Ns <= (Vmax_System/V_cell) UB(3) = 90; % Maximum discharge ratio of the ultracapacitor bank, d_UCbank = 90 UB(4) = 3; % Maximum discharge current from the ultracapacitor bank, i_UCbank <= 3 UB(5) = length(capData);

%% Mixed Integer Optimization IntCon = [1,2,5]; opts = gaoptimset('PopulationSize',150, 'Generations',200, 'EliteCount',10,... 'TolFun', 1e-8, 'PlotFcns', @gaplotbestf);

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[xOpt,fval,exitflag] = ga(@(x)ObjectiveFunction_Database_v11(x,capData),... nvars,[],[],[],[],LB,UB,@(x)ObjectiveFunction_Database_v11_constraint(x ,capData,massLimit),IntCon,opts); %energy (joules) available

%% Solution output disp(' ') disp('The Genetic Algorithm (GA) has found the optimal solution: ') disp([' - The optimal ultracapacitor from the database = line item #' num2str(xOpt(5))]) disp([' - The number of ultracapacitors in parallel (Np) = ' num2str(xOpt(1))]) disp([' - The number of ultracapacitors in series (Ns)= ' num2str(xOpt(2))]) disp([' - The discharge ratio of the ultracapacitor bank (D) = ' num2str(xOpt(3))]) disp([' - The amplitude of the discharge current (I) = ' num2str(xOpt(4))])

%% The Objective Function % F = (1/2 * C_cell * (Np/Ns) * (V_cell*Ns)^2 * (1 - (d_system/100)^2 )) * 1 - 2 * R_cell * (Ns/Np) * (i_system/(V_cell*Ns)) * (100/(100+d_system))

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APPENDIX B: OBJECTVE FUNCTION IMPLEMENTATION IN

MATLAB

Appendix B contains the “.m” file that defines the objective function described mathematically by equation (5-25).

%% For reference purposes only: Definition of search variables % x(1) = Np (number of ultracapaciotrs in parralel) % x(2) = Ns (number of ultracapaciotrs in series) % x(3) = d_system (discharge ratio of the ultracapcitor system) % x(4) = i_system (discharge current of the ultracapacitor system) % x(5) = capacity, voltage, and ESR of available capacitors

%% Objective Function function F = ObjectiveFunction_Database_v11(x,capData) voltage = capData(x(5),1); capacity = capData(x(5),2); esr = capData(x(5),3);

% Calculation of Energy % The Objective Function % F = (1/2 * C_cell * (Np/Ns) * (V_cell*Ns)^2 * (1 - (d_system/100)^2 )) * 1 - 2 * R_cell * (Ns/Np) * (i_system/(V_cell*Ns)) * (100/(100+d_system)) F = -( (1/2*capacity*(x(1)/x(2))*(voltage*x(2))^2*(1-(x(3)/100)^2)) * ... (1-2*esr*(x(2)/x(1))*(x(4)/(voltage*x(2)))*(100/(100+x(3)))) );

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APPENDIX C: OBJECTVE FUNCTION CONSTRAINTS

IMPLEMENTATION IN MATLAB

Appendix C contains the “.m” file that defines the constraints for the objective function described mathematically by equation (5-25).

%% Constraints of the objective function % equation for the Mass Constraint: Np * Ns * 0.5kg <= 10 kg or Np * Ns * 0.5 - 10 <= 10 % equation for the Volume Constraint: TBD function [c, ceq] = ObjectiveFunction_Database_v11_constraint(x,capData,massLimit) % massLimit = 1; mass = capData(x(5),4); c = x(1)*x(2)*mass - massLimit; % Mass constraint for the ultracapacitor bank: Np * Ns * 0.5kg <= 10 kg or Np*Ns*0.5-10<=10 ceq = [];

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APPENDIX D: COPYRIGHT PERMISSIONS

Appendix D contains the copyright permissions that were granted for some of the content used in this dissertation.

Permission granted for content re-used in Figure 4.

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Permission granted for content re-used in Figure 5.

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Permission granted for content re-used in Figure 30 and Figure 31.

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Permission granted for content modification and adaptation in Figure 36.

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Permission granted for content re-used in Figure 43.

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Permission granted for content re-used in Figure 61.

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Permission granted for content re-used in Figure 106.

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