PRELIMINARY SIZING, FLIGHT TEST, and PERFORMANCE ANALYSIS of SMALL TRI-ROTOR VTOL and FIXED-WING UAV a Thesis Pr

PRELIMINARY SIZING, FLIGHT TEST, AND PERFORMANCE

ANALYSIS OF SMALL TRI-ROTOR VTOL AND FIXED-WING UAV

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A Thesis

Presented to the

Faculty of

San Diego State University

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In Partial Fulfillment

of the Requirements for the Degree

Master of Science

Aerospace Engineering

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Arexy Monterroso

Fall 2018

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DEDICATION

To my parents, for your endless work to provide this opportunity, and to my family, in hopes of providing motivation for higher education.

ABSTRACT OF THE THESIS

Preliminary Sizing, Flight Test, and Performance Analysis of Small Tri-Rotor VTOL and Fixed-Wing UAV by Arexy Monterroso Master of Science in Aerospace Engineering San Diego State University, 2018

Mini unmanned aerial vehicles (UAVs) have become increasing popular with the advancement and availability of commercial electronics. These advancements have led to recent developments in aerial vehicles with both vertical-takeoff-and-landing (VTOL) and forward-flight capabilities. A fixed-wing (FW) aircraft can have a thrust-to-weight of 0.1 or lower, while VTOL air vehicles have a thrust-to-weight of 1.2 or higher. Therefore, a VTOL air vehicle must use a lifting wing to extend its endurance. This paper aims to bridge the gap between typical multi-rotor and fixed-wing UAVs by applying sizing estimation methods to design a tri-rotor UAV. The selected tri-rotor configuration is an open-propeller setup with two front tilting-motors that operate in both VTOL and fixed-wing flight, and a rear asymmetric rotor that only operates in VTOL mode. Wind tunnel testing for the propeller’s transitional forces provides insight into the operational envelope of the aerial vehicle during the outbound and inbound transition. The actual vehicle weight is within 3.3% of the sizing’s predicted value of 1.762 kg. Performance of hover and forward flight is presented, and the aerial vehicle’s transition capability is proved. Flight testing shows that the energy consumption is larger than expected, indicating that the propeller efficiency is lower than predicted in the sizing.

TABLE OF CONTENTS

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ABSTRACT ...... v LIST OF TABLES ...... viii LIST OF FIGURES ...... ix NOMENCLATURE ...... xiii ACKNOWLEDGEMENTS ...... xvi CHAPTER 1 INTRODUCTION ...... 1 1.1 Motivation for Integration of VTOL and FW Flight Capabilities ...... 1 1.2 Historical Background of UAVs ...... 1 1.3 Categorizing UAVs by Range ...... 1 1.4 Launch Methods of Small Fixed-Wing UAVs ...... 5 1.5 Hybrid UAVs ...... 5 1.6 Demand of VTOL UAVs ...... 6 1.7 Tilt-Rotor UAV ...... 7 1.8 UAV Preliminary Sizing Estimation ...... 8 2 SIZING METHODOLOGY ...... 10 2.1 Mission Profile ...... 10 2.2 Design Considerations ...... 11 2.3 Design Process ...... 13 2.4 Battery Type...... 14 2.5 Battery Energy ...... 16 2.6 Choosing an Airfoil...... 18 2.7 Preliminary Wing Lift Calculations ...... 20 2.8 Drag Calculations...... 23 2.9 Constraint Analysis ...... 24

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2.10 VTOL Propulsion Sizing ...... 26 2.11 Propulsion Mass Calculation ...... 31 2.12 Mission Analysis (Battery Mass Calculation) ...... 32 2.13 Total Mass Calculation ...... 34 2.14 Sizing Results...... 35 2.14.1 Design Choices ...... 35 2.14.2 Constraint Analysis Results ...... 36 2.15 Horizontal Tail Sizing ...... 39 2.16 Vertical Tail Sizing ...... 44 3 BUILDING THE PROTOTYPE ...... 48 3.1 Electronic Component Selection...... 48 3.2 Final Vehicle Prototype Layout ...... 52 3.3 Materials and Prototyping Techniques ...... 52 3.4. Accuracy of Final UAV Weight ...... 56 4 PROPELLER WIND TUNNEL TESTING...... 58 4.1 The Wind Tunnel ...... 58 4.2 Experimental Setup ...... 59 4.3 Static Testing ...... 61 4.3.1 Static Testing Propeller Comparison ...... 65 4.3.2 Ducted Fan Consideration...... 69 4.4 Wind Tunnel Transition Testing ...... 71 5 FLIGHT TEST – HOVER ...... 75 5.1 Input Parameters for OpenAeroVTOL ...... 75 5.2 Hover Test Data ...... 76 5.3 Investigation of VTOL Disk Loading ...... 81 5.4 Design Modifications to Improve Hover Stability...... 82 6 FLIGHT TEST – FORWARD FLIGHT...... 86 7 FLIGHT TEST – TRANSITION TESTING ...... 91 8 CONCLUSION ...... 94 REFERENCES ...... 97 APPENDIX FW FLIGHT RAW DATA PLOTS ...... 100 viii

LIST OF TABLES

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Table 2.1. Flight Time, Distance, and Battery Type for Commercially Available Quadcopters ...... 16 Table 2.2. List Existing Panel Codes ...... 22 Table 2.3. Survey of Area Ratio of Existing, along with Available Data for Aspect Ratio as Reference ...... 27 Table 2.4. Motor Weight Parameters ...... 31 Table 2.5. Aerodynamic Parameters for Preliminary Sizing ...... 36 Table 2.6. Weight Estimation Results...... 39 Table 2.7. Wing and Propulsion Results ...... 39 Table 2.8. Input Values for the Vertical Tail Sizing ...... 46 Table 2.9. Output Values for the Vertical Tail Sizing ...... 47 Table 3.1. FrSKY Sensors Onboard UAV ...... 51 Table 4.1. ATI Mini45-E Measurement Uncertainty...... 60 Table 4.2. Propeller Transition Test Plan Variables ...... 71 Table 5.1. Required Input Proportional and Integral Gains for Control System ...... 76 Table 6.1. Performance Results for FW Flight ...... 87

LIST OF FIGURES

PAGE

Figure 1.1. Operating altitudes and endurance of various UAV...... 2 Figure 1.2. Northrop Grumman Global Hawk (left) and General Atomics Predator B (right)...... 2 Figure 1.3. Northrop Grumman MQ-5B Hunter (left) and Denel Seeker II (right)...... 3 Figure 1.4. Northrop Grumman MQ-8C Fire Scout (left) and Schielbel Cam-copter S100 (right)...... 3 Figure 1.5. Lockheed Martin Stalker (left) and IAI Pioneer (right)...... 4 Figure 1.6. Boeing V22 Osprey in VTOL (left) and Forward Flight (right) modes...... 5 Figure 1.7. Lockheed Martin F-35 in VTOL mode...... 6 Figure 1.8. Arcturus UAV JUMP 20 (left) and Pigeon-V (right)...... 6 Figure 1.9. DJI Phantom 3 Standard (left) DJI Inspire 2 (right)...... 7 Figure 1.10. Front view of tilt-rotor flow field in hover, outside of ground effect...... 8 Figure 1.11. Uber Elevate eCRM-002 concept vehicle...... 9 Figure 2.1. Range for mini fixed wing UAVs...... 10 Figure 2.2. Mission profile for initial preliminary sizing...... 11 Figure 2.3. OpenVSP preliminary design concept 1...... 12 Figure 2.4. OpenVSP preliminary design concept 2...... 12 Figure 2.5. OpenVSP preliminary design concept 3...... 13 Figure 2.6. OpenVSP preliminary design – final concept...... 14 Figure 2.7. Preliminary sizing method for UAV with VTOL and FW flight capabilities...... 15 Figure 2.8. Survey of the variation of mass versus battery capacity of LiPo batteries...... 17 Figure 2.9. Lift Curve for NACA 4412, 4415, and 4418...... 19 Figure 2.10. Drag Polar for NACA 4412, 4415, and 4418...... 19 Figure 2.11. Airfoil geometry of NACA 4412, 4415, and 4418...... 20 Figure 2.12. Comparison of Lift Curve for 2D and 3D models...... 22

Figure 2.13. VSAERO model of the UAV...... 23 Figure 2.14. Example of a constraint diagram with cruise, climb, ceiling, and stall restrictions...... 25 Figure 2.15. Propeller efficiency as a function of thrust for small UAVs...... 28 Figure 2.16. Disk loading as a function of takeoff mass for small UAVs...... 28 Figure 2.17. Simple momentum model for propeller flow...... 29 Figure 2.18. Flow properties inside control volume used for Figure 2.17...... 30 Figure 2.19. Maximum lift-to-drag ratio trends...... 37 Figure 2.20. Wetted area ratios...... 37 Figure 2.21. Constraint diagram for final VTOL-FW UAV design...... 38 Figure 2.22. VSAERO output pressure distribution over fuselage and horizontal tail...... 40 Figure 2.23. VSAERO output pressure distribution over wing and horizontal tail...... 41 Figure 2.24. Moment coefficient, CMY, for the initial design of horizontal tail...... 41 Figure 2.25. Constraint diagram for the horizontal tail...... 42 Figure 2.26. Impact of horizontal stabilizer placement on longitudinal moment coefficient, CMY, for two different longitudinal distances...... 43 Figure 2.27. Variation of lift versus moment for 3 different tail configurations. CG is assumed at wing quarter chord...... 43 Figure 2.28. Effect of elevator trim on the CMY vs CL curve for UAV...... 44 Figure 2.29. Mean aerodynamic chord of a tapered wing...... 46 Figure 2.30. Planform view for one of the two vertical stabilizers...... 47 Figure 3.1. KK2.1.5 multi-rotor flight control board...... 48 Figure 3.2. Radio transmitter (left) and receiver (right)...... 50 Figure 3.3. Final configuration of electric system for VTOL-FW flight capability...... 50 Figure 3.4. Electronic system bench testing (left) and batteries (right)...... 51 Figure 3.5. UAV layout and configuration...... 53 Figure 3.6. Top-view dimensions of VTOL-FW UAV, in mm...... 54 Figure 3.7. Example of the wing rib and spar installation...... 54 Figure 3.8. Final wing rib design ready to be printed...... 54 Figure 3.9. Cross-section of fuselage...... 55 Figure 3.10. Tilting mechanism for front propulsion assembly...... 55 Figure 3.11. First iteration of rear motor mount (left) and actual final design (right)...... 56 Figure 3.12. UAV weight buildup...... 57

Figure 4.1. ISO-view of San Diego State University Wind Tunnel test section...... 58 Figure 4.2. San Diego State University Wind Tunnel test section dimensions...... 58 Figure 4.3. Propeller stand for installation in the wind tunnel...... 59 Figure 4.4. ATI Mini45-E Force and Moment Load cell...... 60 Figure 4.5. Actual propeller setup inside the wind tunnel...... 61 Figure 4.6. Top view of propeller setup in wind tunnel...... 61 Figure 4.7. Static thrust test results for 10x4.5 propeller...... 62 Figure 4.8. Motor current draw for 10x4.5 propeller during static testing...... 63 Figure 4.9. Available battery voltage for 10x4.5 propeller during static testing...... 63 Figure 4.10. 10x4.5 propeller power consumption during static testing...... 64 Figure 4.11. Static thrust coefficient (left) and static power coefficient (right) for 10 inch propellers...... 66 Figure 4.12. Propeller efficiencies...... 66 Figure 4.13. Static thrust comparison of two propellers...... 67 Figure 4.14. Static testing comparison of motor current draw and available battery voltage...... 67 Figure 4.15. Static testing comparison of propeller power consumption...... 68 Figure 4.16. Comparison of static thrust coefficients (left) and static power coefficients (right)...... 68 Figure 4.17. Comparison of propeller efficiencies...... 69 Figure 4.18. 64mm electric ducted fan...... 70 Figure 4.19. EDF thrust test results...... 70 Figure 4.20. EDF voltage and current draw test results...... 70 Figure 4.21. Propeller forces during transition...... 72 Figure 4.22. Propeller torques during transition...... 73 Figure 4.23. Propeller lifting force component during transition...... 74 Figure 5.1. Inputs for OpenAeroVTOL...... 75 Figure 5.2. Hover testing results...... 77 Figure 5.3. Energy consumption rate for hover test results...... 79 Figure 5.4. Rate of energy consumption for sizing and test results...... 80 Figure 5.5. JavaProp results for propeller in hover...... 81 Figure 5.6. Disk Loading regression models for tri-copters and quadcopters...... 82 Figure 5.7. Demonstration of yaw control in VTOL model...... 83

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Figure 5.8. Balsa wood spar deflection leading to yaw instability...... 84 Figure 5.9. Vibration damper for flight control board...... 85 Figure 6.1. UAV with fitted landing gears for FW flight testing...... 86 Figure 6.2. GPS data from FW flight test...... 87 Figure 6.3. Typhon UDX air vehicle design in FW mode...... 88 Figure 6.4. Typhon UDX lift and drag coefficients...... 89 Figure 6.5. Typhon UDX lift-to-drag ratio...... 90 Figure 7.1. First test of VTOL to FW flight...... 91 Figure 7.2. Progression of UAV transition from FW flight (left) to 45° motor-tilt transition (middle) to VTOL (right)...... 92 Figure A.1. FW flight - Pilot signal inputs...... 100 Figure A.2. FW flight - Power draw...... 100 Figure A.3. FW flight - Ground altitude from GPS...... 101 Figure A.4. FW flight - Ground speed data from GPS...... 101 Figure A.5. FW flight - Total altitude data from GPS...... 101 Figure A.6. FW flight - Total current draw...... 102 Figure A.7. FW flight - Battery supply voltage...... 102 Figure A.8. FW flight - Left motor RPM...... 102

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NOMENCLATURE

퐴푅 = Aspect ratio 푏 = Wingspan 퐶 = Battery capacity 퐶퐺 = Center of Gravity

퐶퐷 = Lift coefficient

퐶퐿 = Lift coefficient

퐶푀 = Moment coefficient

퐶푃 = Power coefficient

퐶푇 = Thrust coefficient 푐 = Wing chord length 푐̅ = Mean aerodynamic chord 퐷 = Drag 퐷퐿 = Disk loading

퐷푝 = Propeller diameter

퐸푏푎푡푡 = Energy of battery, W-h

퐸푠푝푒푐 = Specific energy of battery, W-h/kg 퐸, 퐹, 퐾 = Empirical values 푒 = Oswald efficiency factor

퐹푥,푦,푧 = Forces in x, y, and z

푓푖푛푠푡푎푙푙 = Multiplying factor for installation effects

푓푢푠푎푏푙푒 = Ratio of battery usable energy to total stored energy 푔 = gravity ℎ = height 퐼 = Current 퐿 = Lift

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ℓ = Distance from CG to aerodynamic Center 푀퐹 = Mass fraction

푀푇푂 = Takeoff mass

푚표 = Lift-slope of the two-dimensional airfoil

푛푝푟표푝푠 = Number of propellers 𝑃 = Power 𝑃̅ = Pressure 𝑃푊푀 = Pulse Width Modulation 𝑃⁄푊 = Power to weight ratio 푞 = Dynamic pressure 푅 = range 푅/퐶 = Rate of climb 푆 = Wing reference area 푆퐵푈푆 = Serial Bus

푆푝 = Propeller area 푠 = Number of battery cells 푇 = Thrust

푇푀퐹 = Multiplying factor for the thrust-to-weight ratio

푇푥,푦,푧 = Torques in x, y, and z 푇⁄푊 = Thrust to weight ratio 푡 = time 푉 = Velocity

푉∞ = Freestream velocity

푉퐻푇 = Horizontal tail volume coefficient

푉푉푇 = Vertical tail volume coefficient 푣 = battery voltage 푊 = Weight 푊⁄푆 = Wing loading 푌̅ = Location of mean aerodynamic chord 푦 = Distance from the midspan to the wingtip

훼 = Angle of attack

Γ푚푎푥 = Maximum vorticity 휂 = Efficiency λ = Taper ratio 휌 = Air density

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ACKNOWLEDGEMENTS

I would like to first thank Dr. Joseph Katz for giving me the opportunity to embark on this adventure. His vision, expertise, and mentorship have paved the road to making this project possible. I would like to thank Mitchell, Lindsay, Bao, Rommel, and Oliver, who were part of the senior VTOL team that provided continued support for this project. They were instrumental in providing the tools, assisting with CAD modeling, implementing Additive Manufacturing techniques, as well as hosting the building meetings, and participating in the exciting early morning flight tests. I would like to thank Eric, Ivan, Paul, and the rest team that helped in developing the tools required for testing at the San Diego State University Wind Tunnel. I would also like to thank my thesis committee, including Joseph Katz, Allen Plotkin, and Sahar Ghanipoor Machiani. Thank you for taking the time to review and provide feedback on this project. Finally, I’d like to thank God, my family, and my friends for their support. My mother and father, for constantly encouraging me on this journey and for their financial support. My girlfriend Diana, for joining me on this chapter of my life and being patient, providing support, and giving me advice. And all the friends in and out of school that have provided fun and helped me relax during stressful times.

CHAPTER 1

INTRODUCTION

1.1 MOTIVATION FOR INTEGRATION OF VTOL AND FW FLIGHT CAPABILITIES The integration of VTOL into a fixed-wing aircraft is driven by both the air vehicle’s application and the mission’s endurance requirement. VTOL air vehicles require much more thrust because at minimum, the lift must be equal to weight. In forward flight air vehicles, the thrust must be able to accelerate the vehicle so that the wing creates the lifting force during flight. Typical thrust-to-weight ratios for fixed-wing aircraft is 0.1 or less, while VTOL air vehicles must have thrust-to-weight of at least 1. The order-of-magnitude difference between the thrust-to-weight implies a larger power consumption in VTOL air vehicles, which ultimately leads to a shorter endurance and range for the same weight vehicle.

1.2 HISTORICAL BACKGROUND OF UAVS Over the past several decades, the rapid evolutions in electronic components have facilitated the development of unmanned aerial vehicles (UAV). The benefits of UAVs include eliminating the requirement of an onboard pilot, which in turn, allows the vehicles to carry larger usable payloads and benefit from longer endurance. As such, when comparing the operating environments of UAVs to manned air vehicles (MAV), as depicted in Figure 1.1 [1], the endurance of UAVs greatly exceeds that of MAVs.

1.3 CATEGORIZING UAVS BY RANGE There are six general categories of UAV ranges which are as follows: Long Range, Medium Range, Close Range, Mini UAV, Micro AV, and Nano AV. Within each of these categories, a UAV may be further distinguished by its capability to achieve vertical‐takeoff‐ and‐landing (VTOL). Traditionally, VTOL is characteristic in helicopters (manned or unmanned), whereas non‐VTOL is most common with fixed wing air vehicles.

Figure 1.1. Operating altitudes and endurance of various UAV. Source: [1] Watts, A., Ambrosia, V., and Hinkley, E., “Unmanned Aircraft Systems in Remote Sensing and Scientific Research: Classification and Considerations of Use,” Remote Sensing, Vol. 4, No. 6, 2012, pp. 1671-1692.

Long range UAVs are typically fixed-wing aerial vehicles with efficient cruise performance. Some examples of long range aircraft are shown in Figure 1.2.

Figure 1.2. Northrop Grumman Global Hawk (left) and General Atomics Predator B (right).

Medium range UAVs may be either fixed wing or vertical‐takeoff‐and‐landing (VTOL) vehicles. Some examples of medium-range fixed wing aircraft are shown in Figures 1.3 and 1.4. On the other hand, helicopters fall in the medium-range VTOL category. Since helicopters have VTOL capability, they have been optimized to have their top performance at

Figure 1.3. Northrop Grumman MQ-5B Hunter (left) and Denel Seeker II (right).

Figure 1.4. Northrop Grumman MQ-8C Fire Scout (left) and Schielbel Cam-copter S100 (right). hover and low flight speeds. Per Austin [2], fixed wing aircraft have slightly lower efficiencies than VTOL vehicles because, although they are designed for cruise, their engines are overpowered since they must be able takeoff, land, and get up to cruising speeds. Close-range air vehicles are typically used in battlefield scenarios. These vehicles not only require fast response times, but also operate at much lower altitudes and therefore, experience a lot more turbulence. The purpose of these vehicles is typically close-range surveillance, which means that the vehicle must be designed to operate relatively stable in turbulent environments to maintain favorable sensor operation. Air vehicles with greater weight are more effective at resisting air turbulence. Therefore, a quick analysis done by Austin [2] leads to the conclusion that air vehicles with lower wing loadings experience a greater disturbance to vertical gusts. In the case of close-range air vehicles, the wing loadings are typically under 1000 N/m2, which is where the impact of turbulence is prevalent. Furthermore, close-range air vehicles are large

4 enough that they can’t be hand-launched. They also require special launch and recovery platforms which add complexity to the system.

Figure 1.5. Lockheed Martin Stalker (left) and IAI Pioneer (right).

The two categories of close-range/battle air vehicles are VTOL and Non-VTOL. As previously mentioned, non-VTOL requires long runways and/or launch platforms in order to prevent oversizing the engines. According to Austin [2], VTOL air vehicles (i.e. helicopters) are better suited for close-range /battle field scenarios because of the versatility provided by the VTOL capability in these rapid-deployment environments. Mini UAVs are typically less than 10 kg and are characterized by their ability to be back-packed – many Radio-Controlled hobby air vehicles fall in this range. In the recent past, there has been a lot of crossover between close-range/battlefield and mini UAV categories. Fixed-wing mini UAVs are usually under 6 kg which means that they are light enough to be hand launched. These vehicles tend to be powered by electric motors and batteries. Because of the inherent energy capacity of batteries, the limiting factor in mini UAVs is the battery weight. In fixed wing air vehicles, the battery weight is integrated into the system such that it can still be hand-launched while meeting mission requirements. On the other hand, the are no mini VTOL UAVs that have been adopted by the military. The target range of this paper will be in the mini UAV VTOL category. Micro air vehicles are typically under 15 cm (6 inches) and come in all shapes and sizes. They include fixed wing, rotary wing, flapping wing, and lift-fan air vehicles. An even smaller category are Nano air vehicles. The Nano AVs typically weight under 10 grams total. Over the past decade, there have been various university and military research projects to develop the technology at this level.

1.4 LAUNCH METHODS OF SMALL FIXED-WING UAVS Depending on the weight and stall characteristics of the UAV, several launch techniques can be employed. Typical methods of launching close-range and mini UAVs are Traditional Runway, Hand Launch, Bungee Cord, Launch Tube, and Catapult. It is typical that the launch and recovery method is a driving factor in the design of a small UAV. In close combat scenarios, the VTOL capability in hybrid vehicles offers the benefit of fast deployment and recovery. Because of their low speed maneuverability, they can operate in environments like forests or highly-populated urban areas. The VTOL capability also reduces the complexity in assisted-launch and recovery methods likes catapults launch tubes.

1.5 HYBRID UAVS Hybrid UAVs combine the capability of helicopters with the speed and endurance provided by fixed wing aircraft. Although they are slightly less efficient than both VTOL and Fixed-wing vehicles, they have the capability of extending the range of operating speeds. These hybrid vehicles have been in development over the past several decades. An example of an MAV is the Boeing V22 Osprey as shown in Figure 1.6.

Figure 1.6. Boeing V22 Osprey in VTOL (left) and Forward Flight (right) modes.

Boeing’s V22 Osprey is a tilt-rotor manned air vehicle that can both hover and cruise. The tilt-rotor capability allows it to extend its range to about 1500 km, and in comparison, the range of the GA Predator B UAV (long-range aircraft) is around 3400 km. The main purpose of these hybrid air vehicles is to eliminate the need for a runway. Lockheed Martin’s F-35B, in Figure 1.7, has recently developed a new capability called Short Takeoff/Vertical Landing (STOVL), in which a lifting ducted fan is used to add the capability of landing in

Figure 1.7. Lockheed Martin F-35 in VTOL mode. areas without runways. However, the F-35 is not a UAV but it does provide long-range flight. Because of the wide availability of electronic components along with rapid prototyping techniques, small hybrid UAVs have become increasingly popular. Some examples of small hybrid UAVs are shown in Figure 1.8. These are similar to traditional air vehicles, with an added propulsion system for VTOL. Note how the VTOL propulsion system is not integrated into the system, therefore creating additional drag and ultimately shortening its endurance.

Figure 1.8. Arcturus UAV JUMP 20 (left) and Pigeon-V (right).

1.6 DEMAND OF VTOL UAVS In the past several decades, the VTOL UAV has become increasingly popular amongst close-range use. The film industry has adopted various forms of VTOL UAVs because of the flexibility and control that they provide at low speeds. However, their range is limited due to the high power draw of multiple motors. Although the current record for a mini quadcopter UAV is currently 141 knots [3], the inherent lack in aerodynamic shape

7 does not allow for good efficiency at these speeds. Their power to weight ratio is typically high enough that the drag is irrelevant for their intended use. Typical quadcopters available for commercial use are shown in Figure 1.9.

Figure 1.9. DJI Phantom 3 Standard (left) DJI Inspire 2 (right).

As the range and endurance requirement of small UAVs is extended, battery weight becomes an issue. For example, the DJI Inspire 2 has a max takeoff weight of 4 kg, max speed of 58.2 knots, and max flight time of 27 minutes. However, it uses 2 batteries for flight so the total battery weight is 1.03 kg. This means the battery accounts for 25% of the max takeoff weight, for a max flight time of 27 minutes. Another design that has been under development over the past several decades is the tilt-wing and tilt-rotor concepts.

1.7 TILT-ROTOR UAV As previously shown in Figure 1.6, the tilt-rotor concept is adapted and developed by Boeing’s V22 Osprey. An extensive study [4] was done on a vehicle similar to the V22 Osprey, except that it has four tilt-rotors instead of the two in the V22 Osprey. Compared to a helicopter, this tilt-rotor will have higher disk loading and downwash velocities. In addition, the large rotors induce a download due to the presence of the wing as seen in Figure 1.10 [4]. In some cases, the download in hover can be around 9% of total rotor thrust (outside of ground effect) [4]. In ground effect, the download can turn into a net upload of about 9%. One possible solution to eliminating the downwash caused by the open-rotor and wing interaction is to use a ducted fan. Ducted fans can potentially eliminate the download during hover, while still benefitting from the upload experienced in ground effect. Boeing’s Phantom Swift is a 1/5 scale VTOL prototype that was developed for The Defense Advanced Research Projects Agency (DARPA). This vehicle design is submitted as a prototype that has VTOL capability, efficient hover, moderately high cruise speeds, and

Figure 1.10. Front view of tilt-rotor flow field in hover, outside of ground effect. Source: [4] Radhakrishnan, A., “An Experimental Investigation of Ground Effect on a Quad Tilt Rotor in Hover and Low Speed Forward Flight,” Ph.D. thesis, Univ. Maryland, College Park, MD, 2006. transports heavy cargo. The prototype has four ducted motors – two fans are integrated into the airframe, and the other two are on the outboard wing and can tilt 90˚ to transition from hover to forward flight. These VTOL technologies can eventually find themselves in the surveillance industry, agricultural surveying, or in companies that offer fast delivery services like Amazon. Another approach in eliminating the downwash caused by the open-rotor and wing interaction is to place the open-rotors away from the wing. A current example of this methodology is Uber’s ongoing development of Uber Elevate, as seen in Figure 1.11 [5]. Uber is a technology platform that connects driver-partners and riders. Their vision is to eventually use VTOL vehicles for transportation in highly populated urban areas, like San Francisco, California. The concept in Figure 1.11 has the capability of tilting the propellers at the wing outboard, so that six propellers are used during hover and two propellers during forward flight.

1.8 UAV PRELIMINARY SIZING ESTIMATION Fixed-wing aircraft sizing estimation methods have been highly refined over the past century. There has also been a great amount of research and development of VTOL-specific air vehicles (i.e. helicopters). In addition, advancements in electronic technologies have become more accessible to small-scale researchers. Small quadcopters, like the ones shown in Figure 1.9, have become increasingly popular in the commercial industry. These small

Figure 1.11. Uber Elevate eCRM-002 concept vehicle. This model was developed using OpenVSP and is courtesy of Uber. Source: [5] Gloudemans, J., McDonald, R., Moore, M., Hahn, A., Fredericks, B., and Gary, A., “Open Vehicle Sketch Pad,” OpenVSP [online], 2018, http://openvsp.org/. quadcopters have typical thrust-to-weight ratios that can be upwards of 10. With these large 푇/푊 ratios, the small instabilities in these quadcopters can be quickly corrected. This project investigates the performance of a tri-rotor VTOL air vehicle a 푇/푊 close to 1. With a small 푇/푊 ratio, the VTOL performance of the air vehicle is sensitive to the placement of the propellers. Therefore, propeller placement is also considered to minimize the interaction with the airframe. There have been recent developments that incorporate this hybrid VTOL-FW (fixed wing) technology by integrating a quadcopter setup into an aircraft airframe, as shown in Figure 1.8. However, there is minimal research on tri-rotor aerial vehicles that have both VTOL and fixed-wing (FW) capabilities. The purpose of this paper is to combine fixed-wing aircraft and VTOL sizing estimation techniques, build a prototype, and analyze how well the sizing estimation techniques can predict the air vehicle’s size and performance.

CHAPTER 2

SIZING METHODOLOGY

2.1 MISSION PROFILE Before considering any design vehicles, the flight profile mission must be defined. Because this vehicle will be in the mini VTOL UAV category, the mission profiles range will remain conservative. Figure 2.1 shows the range for various mini UAVs.

Figure 2.1. Range for mini fixed wing UAVs.

A good range for small fixed-wing UAVs appears to be around 10 km. A VTOL UAV requires more power, which means that the range is shorter due to the multiple propellers required for hover. The mission requirements to be used in sizing the vehicle are shown in Figure 2.2. This mission profile can be adapted for both the agricultural and military applications. A typical military application is close-combat surveillance, where the combination of low weight and VTOL capability allows ground troops to carry these UAVs into the battlefield.

Figure 2.2. Mission profile for initial preliminary sizing.

2.2 DESIGN CONSIDERATIONS After choosing a mission profile, different tri-rotor design profiles are considered. Rapid prototyping techniques can be developed using OpenVSP. OpenVSP is a NASA open source parametric geometry software tool that allows users to create 3D designs using common engineering parameters. Another useful functionality incorporated into OpenVSP is the multiple parasite drag models. The parasite drag is useful during the vehicle sizing, which will be explained in the later sections. The fast prototyping nature of this vehicle leans towards using widely available off- the-shelf components. The first consideration is to keep the same model of electric motors to minimize any discrepancy between the output signals and the response between the propellers. The first prototype is shown in Figure 2.3. Typically, the center of gravity for an aircraft is around 25% of the wing’s mean aerodynamic chord (mac). The problem in the design of Figure 2.3 is that the thrust vectors are close to the center of gravity, which means that the hover stability suffers due to the short moment arm. In addition, the added weight from both the tail and rear ducted fan might be too heavy to offset with the electronics at the nose of the fuselage. Another solution is shown in Figure 2.4. This solution allows the thrust vectors to move ahead of the center of gravity. The forward swept wing also moves the spanwise air flow towards the fuselage, which in turns moves the center of pressure rearwards. Moving the center of pressure back allows the center of gravity to remain at 25% mac and maintain

Figure 2.3. OpenVSP preliminary design concept 1.

Figure 2.4. OpenVSP preliminary design concept 2. good hover stability. However, this design has complex structural implications that can potentially add a significant amount of weight. Figure 2.5 shows another possible motor/prop placement strategy. The pods that hold the two front motors give flexibility for the location of the CG. However, the tail placement and integration of the ducted fan into the fuselage both complicate the design and increase the structural weight of the UAV. In addition, the tilting mechanism for the two front motors will have to be heavier due to the robust design that will need to support the ducted fan.

Figure 2.5. OpenVSP preliminary design concept 3.

To avoid obvious weight gains, the design from Figure 2.6 was chosen as the final configuration. The open-prop setup allows a simple tilting mechanism to be used. In addition, the wing-mounted pods that hold the front two propellers will serve two purposes; one is to hold the electronics that power the front propellers, and the second is to attach the horizontal and vertical stabilizers to the aircraft. In VTOL mode all three propellers will be used to hover. The rear propeller will have a servo to control the yaw in VTOL mode. In FW flight, the rear propeller shuts off and the two front propellers are tilted 90° by two separate servos.

2.3 DESIGN PROCESS The purpose of the preliminary design is to converge on the mass, geometry, and power requirements of the vehicle. There are no real sizing methodologies for VTOL tri- copter hybrid UAVs. However, a similar sizing method as presented by Tyan et al. [6] will be adopted. The sizing flow chart for the VTOL-FW UAV is shown in Figure 2.7. The sizing process is primarily driven by the type of mission. The mission can be split into different segments, and each segment analyzed separately. The mission drives the battery mass, which in turn drives the total vehicle mass, geometry, and propulsion. Ideally, an integrated aerodynamic analysis is performed within the mass calculation. However, the sizing in Figure 2.7 provides the opportunity to modify vehicle geometry to try to achieve

Figure 2.6. OpenVSP preliminary design – final concept. optimal aerodynamic characteristics. The following sections will detail each part of the sizing process and its contribution to the overall chart.

2.4 BATTERY TYPE Over the past few decades, the advancement of battery technology has made it possible to build pure VTOL UAVs (tri-copters, quadcopters, etc.) with reasonable flight times (5-30 minutes). Table 2.1 shows the flight time for a few high-end ready-to-fly quad- rotor VTOL UAVs (quadcopters) that are available for commercial use. Because these quadcopters have been highly optimized, their flight times lie on the upper part of the flight- time spectrum. Therefore, it is expected that off-the-shelf components would provide much

Figure 2.7. Preliminary sizing method for UAV with VTOL and FW flight capabilities. lower flight times. In addition, Table 2.1 shows that most high-end quadcopters use Lithium- polymer batteries. LiPo batteries will be considered for this project because they are easily accessible for commercial use, relatively inexpensive, and offer the one of the highest ratios of energy-to-weight. After running initial sizing iterations, a good estimate can be obtained on the required energy for the VTOL-FW UAV. With this initial estimate, market research can be conducted to find the availability of the required LiPo battery type. First, it must be noted that most LiPo batteries are available in series mode. The total battery voltage of a LiPo battery, with cells in series, can be found using

푣푏푎푡푡푒푟푦 = 푣퐿푖푃표,푐푒푙푙 ∗ 푠 where 푠 represents the number of cells in series, and 푣퐿푖푃표,푐푒푙푙 is the nominal LiPo battery cell voltage of 3.7 Volts. For example, a 2S LiPo battery has two cells that are in series, with a total voltage of 7.4. Figure 2.8 shows a survey of various available Lithium-Polymer batteries, done by Bershadsky et al. [7]. Since the electric power is a function of the voltage, then a higher power requirement will require a higher voltage, which

Table 2.1. Flight Time, Distance, and Battery Type for Commercially Available Quadcopters Flight time Control range Name Battery Type [minutes] [m] Blade Chroma Quadcopter 30 2500 Lithium-Polymer (LiPo) Sim Too Pro 30 1000 LiPo DJI Phantom 4 28 3500 LiPo DJI Mavic Pro 27 7000 LiPo DJI Inspire 2 27 7000 LiPo Parrot Bebop 2 25 3200 LiPo DJI Phantom 3 Standard 25 1500 LiPo DJI Phantom 3 Pro 23 3000 LiPo 3DR Solo 22 500 LiPo Yuneec Q500+ 22 2000 LiPo Autel Robotics X-Star 20 1900 LiPo Premium GoPro Karma 20 3000 N/A

means that the number of cells will increase, and ultimately the battery weight will increase for the same mission. From Figure 2.8 [7], the linear relation found between the battery capacity, in mAh, and the battery mass, in kg, is

푀푏푎푡푡 = (푝1 ∗ 푠 + 푝2) ∗ 퐶/1000 (2.1) where p1 is 0.026373 and p2 is 2.0499e-05. The constant s represents the number of cells in series. The battery mass will be derived from the sizing, so Equation 2.1 will help determine the appropriate battery capacity for the mission.

2.5 BATTERY ENERGY

Although LiPo batteries provide high specific energy, 퐸푠푝푒푐, they are still the main limiting factor in VTOL vehicles. Using the survey from Bershadsky et al. [7], the Specify

Energy 퐸푠푝푒푐 of LiPo batteries is around 140 W-h/kg. However, Navarathinam et al. [8] shows that the Specific Energy range of LiPo batteries is 130-250 W-h/kg. In the initial sizing a value of 130 W-h/kg will be assumed to remain conservative. The specific battery energy in Equation 2.2 can be used to verify the specific energy of the battery once test data

Figure 2.8. Survey of the variation of mass versus battery capacity of LiPo batteries. Source: [7] Bershadsky, D., Haviland, S., and Johnson, E., “Electric Multirotor UAV Propulsion System Sizing for Performance Prediction and Design Optimization,” Proceedings of the 57th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, San Diego, CA, 2016, pp. 1-22. has been acquired. In Equation 2.2, the capacity C is in A-h, and the battery mass 푀푏푎푡푡 is in kg.

퐸푠푝푒푐 = 푣푏푎푡푡푒푟푦 ∗ 퐶/푀푏푎푡푡 (2.2)

The available battery energy, 퐸푏푎푡푡, is dependent on the assumed battery specific energy of 130 W-h/kg, and is defined as 푊 퐸 = 퐸 푏푎푡푡 휂 푓 = 퐸 푀 휂 푓 (2.3) 푏푎푡푡 푠푝푒푐 푔 푏푎푡푡 푢푠푎푏푙푒 푠푝푒푐 푏푎푡푡 푏푎푡푡 푢푠푎푏푙푒 where 휂푏푎푡푡 accounts for heating losses. Per Gatti [9], a value of 95% can be used for LiPo batteries. The 푓푢푠푎푏푙푒 is the depth of discharge ratio, which is the ratio of battery usable energy to total stored energy. Navarathinam et al. [8] shows that the energy LiPo battery cells are fully charged at 4.2 V, and fully discharged at 2.8 V. However, fully discharging a LiPo battery significantly decreases both its charge cycles and the capacity retention. Navarathinam et al. [8] also shows that the charge capacity of LiPo batteries can decrease to 75% over six hundred charge cycles at standard atmosphere conditions. In some cases, fully discharging a LiPo can potentially render the battery dead. Most hobbyist will not operate the

18 battery when an individual cell voltage is below 3 - 3.3 V. This means that the 푓푢푠푎푏푙푒 is between 64% and 86%. An average of 75% will be used for 푓푢푠푎푏푙푒.

In summary, the assumed battery specific energy, 퐸푠푝푒푐, will be used to size the battery mass fraction, which in turn yields the battery energy, 퐸푏푎푡푡. With the battery energy, Figure 2.8 and Equation 2.1 can be used to verify that the battery’s combination of voltage and capacity will meet the required battery mass.

2.6 CHOOSING AN AIRFOIL The goal of choosing an airfoil is to have the best possible range. Airfoil trade studies can yield the best range possible for a given set of airfoils. On the other hand, an airfoil optimization can be integrated into the sizing to develop the best case for the input mission and flight parameters. However, the build methods that will be employed will beg the question of whether small changes in the airfoil will drastically change the UAV’s range. To simplify the building process, a standard 4-digit NACA airfoil is chosen. The first digit in a four-series NACA airfoil represents the maximum camber, as a %, of the 2D airfoil chord. The second digit represents the location of the max-camber from the leading edge, and is read in tenths. The third and fourth digits represent the maximum thickness as a percent of the 2D chord. Typically, a higher airfoil thickness slightly delays the stall angle, while higher airfoil camber raises the entire 퐶퐿 − 훼 curve. Figure 2.9 shows the 퐶퐿 − 훼 curve for the NACA airfoils 4412, 4415, and 4418. The analysis is done in XFOIL, along with the cruise conditions for the UAV. Note that the NACA 4418 airfoil displays the best characteristics because it stalls near 14 degrees. Figure 2.10 shows the viscous drag-due-to-lift, which clearly shows how the drag increases as the stall angle is approached. Again, the favorable airfoil is the NACA 4418 because the viscous drag-due-to-lift will always be lower. However, after surveying the build materials, it was decided that the additional weight of the spar required by the thicker airfoil was not worth the small gain in aerodynamic characteristics. Therefore, the NACA 4415 airfoil was chosen for the final design. Figure 2.11 shows a comparison of all three NACA airfoils.

Figure 2.9. Lift Curve for NACA 4412, 4415, and 4418.

Figure 2.10. Drag Polar for NACA 4412, 4415, and 4418.

Figure 2.11. Airfoil geometry of NACA 4412, 4415, and 4418.

2.7 PRELIMINARY WING LIFT CALCULATIONS The two-dimensional lifting characteristics of any airfoil can be calculated using panel methods. XFOIL is a common, open-source software that can easily find the 2D characteristic of an airfoil. However, this software assumes an infinite aspect ratio (2D wing). In reality, the wingtips of a finite wing will produce a vortex that will have an induced downwash on the wing. This wingtip-induced downwash has a larger effect on wings with lower aspect ratios. The Finite Wing Lifting Line model [10] shows that combining the spanwise downwash and an elliptical circulation distribution yields 1 2 2 2Γ푚푎푥 푦 Γ푚푎푥 − [1 − ( ) ] − + (훼(푦) − 훼퐿푂 (푦)) = 0 (2.4) 푚표(푦)푐(푦)푉∞ 푏/2 2푏푉∞ where Γ푚푎푥 is the maximum vorticity, 푚표(푦) is the lift-slope of the two-dimensional airfoil, b is the span, 푉∞ is the freestream velocity, y is the distance from the midspan to the wingtip, 훼(푦) section airfoil’s angle of attack, and 푐(푦) is the chord at each station. For a square wing with no twist, the lift slope 푚표, chord 푐(푦), and section angle of attack 훼(푦) are constant. Equation 2.4 can be reduced to

푐푉∞퐴푅 Γ푚푎푥 = 2퐴푅 1 (훼 − 훼퐿푂 ) (2.5) + 푚표 2

21 where 퐴푅 is the wing aspect ratio. Once an airfoil has been picked, the 푚표 and 훼퐿푂 can be calculated using a program like XFOIL. These values can then be substituted into the lift and drag equations

휋푏 휌푉 Γ 퐿 4 ∞ 푚푎푥 휋퐴푅 퐶퐿 = 1 2 = 1 2 = 4퐴푅 (훼 − 훼퐿푂 ) (2.6) 휌푉∞푆 휌푉∞푆 +1 2 2 푚표 휋 휌Γ2 퐷𝑖 8 푚푎푥 1 푆 2 퐶 = 1 = 1 = 퐶 (2.7) 퐷푖 휌푉2 푆 휌푉2 푆 휋 푏2 퐿 2 ∞ 2 ∞ where 휌 is the air density the operating condition, and 푆 is the wing reference area. Of course, these equations assume that the wing planform is known. Therefore, multiple sizing iterations will allow a convergence on a result. A survey of mini VTOL experimental vehicles shows that an aspect ratio of 5-7 is used. For this UAV, and aspect ratio of 5 will be used. However, as the building method for the wing progresses, it becomes convenient to increase the wing chord length so that the aspect ratio becomes 4.24; the wing chord is increased from 18.4 cm to 21.6 cm. For initial design, the 3D wing lift can be calculated using Equation 2.6. However, as the sizing iterations begins to converge, VSAERO can be used to find the full vehicle’s aerodynamic characteristics. VSAERO is a UNIX based software that is available on the San Diego State University campus. This software uses a panel method to calculate the aerodynamic characteristics of an aircraft. Other existing commercial panel codes are shown in Table 2.2 [11-18]. Another open source software that can find the aerodynamic characteristics is XFLR5 [19], which essentially uses a range of values from XFOIL to interpolate at the user-defined wing sections. In addition, a vortex lattice method adopted by AVL [20] can also be used since it is an open source software. The drawbacks of using AVL are that it doesn’t model thickness, it models all bodies as lifting bodies, and it can’t study the influence of an airplane body on the wing. Figure 2.12 shows the results of several methods for finding preliminary lift-slope values for the UAV. The simplest method is the 2D analysis. After choosing an airfoil, the 3D lift-slope of the wing can be calculated for preliminary analysis. Once a rough estimate of the geometry is known, commercial panel methods like VSAERO can calculate the aerodynamic characteristics for the entire vehicle. To converge on a solution, the VSAERO results can be incorporated into the sizing.

Table 2.2. List Existing Panel Codes Program Year VSAERO [11] 1987 PAN AIR [12] 1990 PMARC [13] 1992 FPA [14] 1996 FastAero [15] 2000 DWFS [16] 2003 CBAERO [17] 2004 APAME [18] 2008 Sources: [11] Maskew, B., “Program VSAERO Theory Document,” NASA TR-4023, September 1987. [12] Epton, M. and Magnus, A., “PAN AIR - A Computer Program for Predicting Subsonic or Supersonic Linear Potential Flows about Arbitrary Configuration Using a Higher Order Panel Method,” NASA TR-3253, December 1981. [13] Ashby, D., Dudley, M., Iguchi, S., Browne, L., and Katz, J., Potential Flow Theory and Operation Guide for the Panel Code PMARC 12, NASA, Washington, DC, 1992. [14] Boschitsch, A., Curbishley, T., Quackenbush, T., and Teske, M., “A Fast Panel Method for Potential Flows about Complex Geometries,” Continuum Dynamics, Inc., TR-MSA005, Ewing Township, NJ, January 1996. [15] Willis, D., “An Unsteady, Accelerated, High Order Panel Method with Vortex Particle Wakes,” Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, MA, 2006. [16] Eller, D. and Carlsson, M., “An Efficient Aerodynamic Boundary Element Method for Aeroelastic Simulations and its Experimental Validation,” Aerospace Science and Technology, Vol. 7, No. 7, 2003, pp. 532-539. [17] Kinney, D., “Aero-Thermodynamics for Conceptual Design,” Proceedings of the 42nd AIAA Aerospace Sciences Meeting, Reno, NV, 2004, pp. 1-11. [18] Filkovic, D., “Graduate Work,” Master’s thesis, Univ. Zagreb, Zagreb Croatia, 2008.

Figure 2.12. Comparison of Lift Curve for 2D and 3D models. 23

Figure 2.12 shows that the theoretical lift-slope from Equation 2.6 matches with the results from XFOIL. The benefits of XFOIL is that it can predict the 2D stall characteristics. Note that both the theoretical 3D and the results from VSAERO can neither predict stall characteristics. Also note that the complete aircraft slope is lower than the theoretical 3D calculation. This phenomenon must be investigated further, but it probably comes from inefficiencies caused by the interactions between the wing, fuselage, and tail. Figure 2.13 shows the VSAERO models used in calculating the lift-slope curve from Figure 2.12.

Figure 2.13. VSAERO model of the UAV.

2.8 DRAG CALCULATIONS During the initial sizing, the parabolic drag model can be used as an initial assumption. The drag model is represented by 2 퐶퐷 = 퐶퐷0 + 푘퐶퐿 (2.8) 1 푘 = (2.9) 휋푒퐴푅 where 퐴푅 is the aspect ratio, 푒 is the Oswald efficiency factor, and 퐶퐷0 is the minimum (zero-lift) drag coefficient. As the design moves from preliminary to conceptual, more complex methods of drag analysis can be adopted.

2.9 CONSTRAINT ANALYSIS The purpose of this project is to combine the constraint analysis of the fixed-wing UAV with the VTOL capabilities, and to study the effectiveness of the predictions. Typically, constraint diagrams are used for fixed-wing aircraft. The constraint analysis begins with looking at the lift, drag, weight, and thrust forces on the aircraft. The effect of these forces can be represented in terms of two functional parameters: the minimum sea level thrust-to-weight (푇푆퐿 /푊푇푂) and the wing loading (푊푇푂/푆푤). The relationships for the constraint diagram can be derived in terms of the minimum sea level thrust-to-weight

(푇푆퐿 /푊푇푂) and then converted to power-to-weight (𝑃⁄푊) using the following relationship [21],

(푇⁄푊)푉 𝑃⁄푊 = (2.10) 휂푝 where V is the velocity and 휂푝 is the propeller efficiency. This relationship becomes important because it allows for a direct comparison to electrical power later in the design process. Ultimately, this analysis aims to establish the shape of the wing and the propulsive requirement of the UAV. In any forward-flight UAV, the takeoff, landing, climb, and cruise requirements typically drive the wing and propulsion system design. As a side note, there are additional regulatory restrictions that must be met based on the type of aircraft and industry in which the UAV will operate. These additional regulations will not be covered in this paper. Figure 2.14 shows an example of how a constraint diagram defines the allowable design space for a forward-flight, fixed-wing UAV. The benefit of electric motors is their independence of air density, which also means that they do not require power normalization to sea level conditions. In addition, the cruise altitude of the UAV is designed to remain within the Federal Aviation Administration’s UAS classification of an Unmanned Aerial System, as specified by both Section 336 and Part 107, which states that the UAS should remain under 400 ft (122 m). Using the parabolic drag model from Equation 2.8, the following constraint equations can be developed. Equation 2.11, derived in Gudmundsson [22], is the required thrust for a given cruise condition.

푇 퐹푊 1 1 ( ) = 푞퐶퐷 + 푘 (푊⁄푆) (2.11) 푊 푐푟푢푖푠푒 0 (푊⁄푆) 푞 1 푞 = 휌푉2 (2.12) 2

Figure 2.14. Example of a constraint diagram with cruise, climb, ceiling, and stall restrictions. where 푞 is the dynamic pressure at the selected cruise airspeed and altitude. Similarly, the thrust-to-weight ratio for a desired rate-of-climb is defined [22] 퐹푊 푇 푉푉 푞 푘 ( ) = 퐹푊 + 퐶퐷 + (푊⁄푆) (2.13) 푊 푐푙푖푚푏 푉푟표푐 (푊⁄푆) 0 푞 where 푉푉 is the desired vertical speed and can be an input from the user or from the design requirements. 푉푟표푐 is the best rate-of-climb airspeed for a propeller-powered aircraft, and can be calculated using the following equation [22].

퐹푊 2 푘 푉푟표푐 = √ (푊⁄푆)√ (2.14) 휌 3퐶퐷0

Equations 2.13 and 2.14 can also be used to define a rate of climb at the service ceiling. From the FAA pilot handbook, the service ceiling is defined as the highest altitude at which the airplane can maintain a steady rate-of-climb of 100 fpm. Therefore, the ceiling rate-of-climb will be 0.5 m/s for this UAV. The other major constraint for forward flight is the stall speed, which is calculated using Equation 2.15, 1 (푊⁄푆)퐹푊 = 휌푉2 퐶 (2.15) 푠푡푎푙푙 2 푠푡푎푙푙 퐿푚푎푥 where 푉푠푡푎푙푙 is the stall velocity and 퐶퐿푚푎푥 is the maximum lift coefficient. In typical fixed- wing forward-flight aircraft, 퐶퐿푚푎푥 is assumed to occur during either takeoff or landing, and with a full flap deflection. However, the purpose of VTOL UAVs is to avoid any takeoff and

26 landing constraints associated with fixed-wing aircraft. Sizing with the stall requirement helps determine the transition from VTOL to FW. A direct method of using the stall wing loading in the constraint analysis is to define both the required minimum speed 푉푠푡푎푙푙 and the max lift coefficient 퐶퐿푚푎푥 . In the case of this

UAV, the lack of flaps means that the actual wing’s 퐶퐿푚푎푥 can be used for the analysis. For preliminary estimations, the 2D estimation from XFOIL can be used, corrected for the inefficiencies caused by the wingtip vortices in the 3D wing. As shown in Figure 2.14, the climb, cruise, ceiling, and stall will be the driving requirements for the constraint diagram. The constraint diagram is not only connected to the other design modules but it also provides a visual feedback for the allowable design space of the UAV.

2.10 VTOL PROPULSION SIZING The forces on the UAV in VTOL mode are the thrust, weight, and drag. 푇 = 푊 + 퐷 A flat plate model is appropriate for the VTOL model because it assumes the highest possible drag during climb and descent. The drag coefficient as a function of the angle-of-attack 훼 for a flat plate is shown in Equation 2.16. 2 퐶퐷 = 2 sin 훼 (2.16) In VTOL mode, 훼 is 90°, which means that the drag coefficient is 2. Substituting the 1 equation for drag, 퐷 = 휌푉2푆퐶 , and the flat plate drag coefficient assumption in Equation 2 퐷 2.16, the thrust equation becomes 푉푇푂퐿 푉푇푂퐿 2 푇푐푙푖푚푏 = 푊 + 휌(푉푟표푐 ) 푆 (2.17) 푉푇푂퐿 where the maximum VTOL rate-of-climb 푉푟표푐 is an input requirement by the designer. Before proceeding it must be noted that three statistical models are used in this analysis. The first model uses the historical data for the area ratio, 푆푝푟표푗⁄푆, of existing aircraft as shown in Table 2.3. The area ratio is defined as ratio of the total aircraft projected area to the wing area. Note that data for the aspect ratio is added as a reference. The range of values for the area ratio lie between 1.3 and 1.4. Since the required VTOL thrust is directly related to the area ratio, a value of 1.4 will be used to remain

Table 2.3. Survey of Area Ratio of Existing, along with Available Data for Aspect Ratio as Reference 2 Aircraft Model Type 푺풑풓풐풋/푺 S [m ] AR UAV Factory Penguin B FW 1.41 0.79 13 TAM 5 FW 1.29 0.71 5.1 Precision Hawk Lancaster 3 FW 1.39 0.33 4.7 Autel Robotics Kestrel FW-VTOL 1.24 0.82 15 Arcturus Jump-20 FW-VTOL 1.30 2.62 12 Arcturus Jump-15 FW-VTOL 1.39 N/A N/A Aerosonde HQ FW-VTOL 1.46 N/A N/A Pigeon-V FW-VTOL N/A N/A 7.5 Falcon-V (version 1) FW-VTOL N/A 1.12 8 Falcon-V (version 2) FW-VTOL N/A 1.54 13 Source: [6] Tyan, M., Nguyen, N., Kim, S., and Lee, J., “Comprehensive Preliminary Sizing/Resizing Method for a Fixed Wing – VTOL Electric UAV,” Aerospace Science and Technology, Vol. 71, December 2017, pp. 30-41. conservative. As the vehicle design process converges, the actual value can be used to finalize the iterations. Further manipulation of Equation 2.17 yields the VTOL thrust-to-weight equation

푉푇푂퐿 푇 1 푉푇푂퐿 2 ( ) = 푇푀퐹 (1 + 휌(푉푟표푐 ) (푆푝푟표푗⁄푆)) (2.18) 푊 푐푙푖푚푏 푊⁄푆 where 푇푀퐹 is a multiplying factor for the thrust-to-weight ratio. 푇푀퐹 allows designers to choose the amount of flexibility on the UAV thrust performance in VTOL mode. A multiplying factor of 1.1 will be used for this vehicle. As a reference, the 푇푀퐹 of race quadcopters can be as high as 5 [6]. The flight-test phase will prove the importance of this value in the performance of the UAV in VTOL mode. The second statistical model for the propeller efficiency is shown in Figure 2.15. The experimental data gathered by Tyan et al. [6] for this model includes 85 motor- propeller combinations. The regression model developed for propeller efficiency is 0.0793 휂푝 = 0.4742 ∗ 푇푚 (2.19)

푇푉푇푂퐿 푇푚 = 푉푇푂퐿 (2.20) 푛푝푟표푝푠 푉푇푂퐿 where 푇푚 is the thrust of one motor, and 푛푝푟표푝푠 is the number of active propellers during VTOL mode. The correlation coefficient for this regression model is R = 0.6. With the motor thrust, the third statistical model for the disk loading can be implemented. The disk loading is

Figure 2.15. Propeller efficiency as a function of thrust for small UAVs. Source: [6] Tyan, M., Nguyen, N., Kim, S., and Lee, J., “Comprehensive Preliminary Sizing/Resizing Method for a Fixed Wing – VTOL Electric UAV,” Aerospace Science and Technology, Vol. 71, December 2017, pp. 30-41. the amount of force per total propeller disk area that the UAV is subjected to. Figure 2.16 shows the effect of takeoff mass on the propeller disk loading.

Figure 2.16. Disk loading as a function of takeoff mass for small UAVs. Source: [6] Tyan, M., Nguyen, N., Kim, S., and Lee, J., “Comprehensive Preliminary Sizing/Resizing Method for a Fixed Wing – VTOL Electric UAV,” Aerospace Science and Technology, Vol. 71, December 2017, pp. 30-41.

The correlation coefficient for this regression model is R = 0.87. The equation is

퐷퐿 = 3.2261푀푇푂 + 74.991 (2.21)

29 where 푀푇푂 is the takeoff mass, in kg. The area 푆푝 and diameter 퐷푝 for one propeller can be calculated using

푊푇푂 푆푝 = 푉푇푂퐿 (2.22) 퐷퐿∗푛푝푟표푝푠

4푆 퐷 = √ 푝 (2.23) 푝 휋

To find the power required for the propeller, the induced velocity 푉푖 must be derived using the momentum theory. Using momentum theory, an analysis [22] can be conducted for the air stream tube through the propeller as seen in Figure 2.17. The ideal properties of the air are shown in Figure 2.18.

𝑃0 0 Control Volume 1 2 3 𝑃0

푉0 푉0 푉0

푉3

푉2 T 푆 퐴2 퐴3

𝑃1 𝑃2

Figure 2.17. Simple momentum model for propeller flow.

The assumptions in momentum theory are: 1. The propeller is assumed to be an infinitesimally thin actuator disk that offers no resistance to air passing through it 2. There is uniform acceleration across and uniform loading at every point on the thin disk 3. The flow stream tube does not experience leakage to the ambient conditions 4. Flow outside the stream tube has constant stagnation pressure which consequently means that no work is done on it

푉3

푉1, 푉2

푉0

𝑃2

𝑃0

𝑃1

Pressure added by propeller

𝑃푠푡푎푔푛푎푡푖표푛

Figure 2.18. Flow properties inside control volume used for Figure 2.17.

5. At the stream tube inlet and exit, the streamlines are parallel and pressures on the inside match far-field pressure 6. Irrotational 7. Incompressible 8. Inviscid (no drag or momentum diffusion) With these assumptions, the momentum and mass balance equations, Bernoulli’s principle eventually lead to the velocity relation

(푉 +푉 ) 푉 = 3 0 2 2 where 푉0 is the upstream far-field velocity, 푉3 is the downstream far-field velocity, and 푉2 is the velocity at the propeller inlet. A new relationship for the propeller-induced velocity 푉푖 is introduced as

푉푖 = 푉2 − 푉0 = 푉3 − 푉2 Using the momentum balance, the equation for the propeller-induced velocity can be derived.

2 푉푉푇푂퐿 푉푉푇푂퐿 2 푉 = − 푟표푐 + √( 푟표푐 ) + (푉 ) (2.24) 푖 2 2 푖ℎ During hover the rate of climb is zero, and the velocity induced during hover is

푇푚 푉푖ℎ = √ (2.25) 2휌푆푝

The power required during VTOL mode is a function of the induced velocity [22] as is calculated using

푉푇푂퐿 푉푇푂퐿 푇 ∗푉𝑖 𝑃푟푒푞 = (2.26) 휂푝

2.11 PROPULSION MASS CALCULATION 푉푇푂퐿 The max motor power is 𝑃푚표푡,푚푎푥 = 𝑃푟푒푞 /푛푝푟표푝푠. An empirical relationship between the max motor power (kW) and the motor mass (kg) is developed by Gundlach [23].

푊 퐸 푚표푡표푟 1 퐸2 ( ) = 퐹1(𝑃푚표푡,푚푎푥) (푉푚푎푥) (2.27) 푃푚표푡,푚푎푥 where 퐹1, 퐸1, and 퐸2 are empirical parameters, and 푉푚푎푥 is the maximum rated motor voltage. Table 2.4 shows the results for 퐹1, 퐸1, and 퐸2 for different motor types.

Table 2.4. Motor Weight Parameters

Motor Class 퐅ퟏ 퐄ퟏ 퐄ퟐ Brushless ferrite 7.765 –0.632 0.596 Brushed rare earth 8.160 –0.961 1.166 Brushless inrunner 13.17 –0.610 0.067 Brushless outrunner 0.889 –0.288 0.1588 Source: [23] Gundlach, J., Designing Unmanned Aircraft Systems, American Institute of Aeronautics & Astronautics, Reston, VA, 2014.

To adapt fast prototyping techniques, brushless outrunner motors will be considered since they are common and easily accessible. Typically, the motor manufacturer specifies the allowable batteries for safe motor operation. The battery type (ex. LiPo 3S) determines the max rated motor voltage, 푉푚푎푥, because the motor only operates at the battery’s supply voltage. In addition, the motor manufacturer specifies the motor power and/or thrust. Therefore, a few sizing iterations should converge to the appropriate range of power that is required from the motor. Careful attention should be placed on the performance of the motor over time; the motor power output can drop as the battery depletes. The mass of the electronic speed controller (ESC) can be calculated using the following empirical relationship [23]

퐸1,퐸푆퐶 푀퐸푆퐶 = 퐹퐸푆퐶(𝑃푚표푡,푚푎푥) (2.28)

-4 where 𝑃푚표푡,푚푎푥 is in kg, and the coefficients 퐹푒푠푐 and 퐸1,퐸푆퐶 are 0.7383 X 10 and 0.8854 respectively. An empirical formula can determine the mass of the propeller [24] using

푉푇푂퐿 0.782 −3 0.391 퐷푝푃푟푒푞 푀푝푟표푝 = 6.514 푋 10 퐾푚푎푡푒푟푖푎푙퐾푝푟표푝푛푝푟표푝푠푛푏푙푎푑푒푠 ( ) (2.29) 1000푛푝푟표푝푠 where 푀푝푟표푝 is in kg, 퐾푝푟표푝 value of 15 is suggested [23] for plastic or composite propellers operating under 37 kW, 푛푝푟표푝푠 is the total number of propellers, 푛푏푙푎푑푒푠 is the number of 푉푇푂퐿 blades, 퐷푝 is propeller diameter in meters, 𝑃푟푒푞 is the max power of all motors. The

퐾푚푎푡푒푟푖푎푙 value can be 1 for plastic, 0.6 for composite, and 1.3 for wood. The propulsion mass is defined as sum of the propeller, motor, and ESC masses.

푊 푀 = 푓 (푛 ( 푚표푡표푟 + 푀 ) + 푀 ) (2.30) 푝푟표푝푢푙푠푖표푛 푖푛푠푡푎푙푙 푚표푡 푔 퐸푆퐶 푝푟표푝 Because VTOL systems with tilting components require additional structural support, the

푓푖푛푠푡푎푙푙 is added as a multiplication factor to account for installation effects. The installation effects cover the mechanical installation and miscellaneous propulsion-related systems. For this UAV, an installation factor of 1.2 is used [23]. If the UAV will have separate propellers for VTOL and FW flight, then the constraint analysis from section 2.9 can yield the minimum power required for FW flight. The FW propeller diameter can be calculated using the following empirical equation from Raymer [21]

4 퐹푊 퐹푊 푃푟푒푞 퐷푝 = 퐾푝 √ 퐹푊 (2.31) 푛푝푟표푝푠

퐹푊 where 퐾푝 is 0.1072, 0.0995, 0.0938 for two-, three-, and four-blade propellers. 푛푝푟표푝푠 is the number of propellers used for FW flight.

2.12 MISSION ANALYSIS (BATTERY MASS CALCULATION) The losses in the electric power absorbed by the propeller are in the propeller design, motor, ESC, and power distribution system. The losses can be represented as

휂푎푙푙 = 휂푝휂푔푒푎푟휂푚표푡표푟휂퐸푆퐶휂푃퐷푆 (2.32) The propeller efficiency can be obtained using Equation 2.19. However, higher- fidelity methods can also be employed to gain better accuracy on the propeller efficiency.

The gear efficiency 휂푔푒푎푟 is omitted since the propeller will connect directly to motor shaft.

The motor efficiency is assumed to be 75%. The ESC efficiency 휂퐸푆퐶 is assumed to be 95%.

The power distribution efficiency 휂푃퐷푆 is assumed to be 95%. Section 2.5 shows the battery efficiency 휂푏푎푡푡 and useable battery energy values 푓푢푠푎푏푙푒. The main source of energy for the system is the LiPo battery. Therefore, the propulsion power will come directly from the available battery power.

𝑃푏푎푡푡 = 𝑃푝푟표푝푢푙푠푖표푛 + 𝑃표푡ℎ푒푟 (2.33)

The propulsion power 𝑃푝푟표푝푢푙푠푖표푛 is the power absorbed by the propellers. The other propulsion power 𝑃표푡ℎ푒푟 is the power required for the subsystems. The other propulsion power is assumed to be small, and therefore negligible, compared to the propulsion power absorbed by the propeller. For level flight, the aircraft thrust power generated by the propeller is 푊 𝑃 = 퐷 ∗ 푉 = 푇푂 ∗ 푉 (2.34) 푇ℎ푟푢푠푡 퐿⁄퐷 Combining Equations 2.33 and 2.34, and including the losses through the electrical system,

푃푇ℎ푟푢푠푡 𝑃푏푎푡푡 = 𝑃푝푟표푝푢푙푠푖표푛 = (2.35) 휂푎푙푙 The endurance equation can then be defined as

퐸 퐸 푀 휂 푓 푡 = 푏푎푡푡 = 푠푝푒푐 푏푎푡푡 푏푎푡푡 푢푠푎푏푙푒 퐿⁄퐷 (2.36) 푃푏푎푡푡 푊푇푂∗푉 where 퐸푏푎푡푡 is defined in Watt-hours and 𝑃푏푎푡푡 in Watts. The mass fraction is the ratio of mass component to total mass.

푀𝑖 푀퐹푖 = (2.37) 푀푇푂

푀푇푂 = ∑푖(푀푇푂 ∗ 푀퐹푖) (2.38) Most electric batteries are defined in Watt-hours, therefore with a little manipulation the energy relationship from Equation 2.3 can be used to obtain the battery mass fraction for maximum endurance. The maximum endurance equation is used for the loiter segment of the mission.

푡 푔 2(푊⁄푆) 푀퐹푙표푖푡푒푟 = 푙표𝑖푡푒푟 √ (2.39) 푏푎푡푡푒푟푦 휂 (퐸 휂 푓 )(퐶3⁄2 ⁄퐶 ) 휌 푎푙푙 푠푝푒푐 푏푎푡푡 푢푠푒푎푏푙푒 퐿푙표𝑖푡푒푟 퐷푙표𝑖푡푒푟 2 where the loiter time 푡푙표푖푡푒푟 is in seconds, the gravity 푔 is in m/s , the specific energy 퐸푠푝푒푐 is in W-s/kg, and the loiter lift and drag coefficients can be found by using panel codes to

34 calculate the loiter conditions of the UAV (see Table 2.2). The cruise segments of the mission can be calculated by multiplying the endurance equation by the velocity, and rearranging

푟푎푛푔푒 푅푔 푀퐹푏푎푡푡푒푟푦 = (2.40) 휂푎푙푙(퐸푠푝푒푐휂푏푎푡푡푓푢푠푒푎푏푙푒 )(퐿⁄퐷) where 푅 is in meters, and 퐿⁄퐷 is the best achievable lift-to-drag ratio during the cruise mission leg. The general form the of battery mass fraction, as shown in Equations 2.41 and 2.42, is used to calculate the FW climb and VTOL climb mission legs.

퐹푊 푐푙푖푚푏,퐹푊 푡푐푙𝑖푚푏,퐹푊푃푐푙𝑖푚푏 푀퐹푏푎푡푡푒푟푦 = (2.41) 휂푎푙푙(퐸푠푝푒푐휂푏푎푡푡푓푢푠푒푎푏푙푒 )푀푇푂

푉푇푂퐿 푐푙푖푚푏,푉푇푂퐿 푡푐푙𝑖푚푏,푉푇푂퐿푃푟푒푞 푀퐹푏푎푡푡푒푟푦 = (2.42) 휂푎푙푙(퐸푠푝푒푐휂푏푎푡푡푓푢푠푒푎푏푙푒 )푀푇푂 During hover, the power is proportional to the thrust times the induced velocity. Using Equation 2.26, the general form of the mass fraction equation can be represented as a function of the UAV’s disk loading.

ℎ표푣푒푟 푡ℎ표푣푒푟 푔 퐷퐿 푀퐹푏푎푡푡푒푟푦 = √ (2.43) 휂푎푙푙 (퐸푠푝푒푐휂푏푎푡푡푓푢푠푒푎푏푙푒 ) 2휌 The equation above represents the total energy consumed by the UAV during hover. ℎ표푣푒푟 To size for worst case scenario, the equation for the hover mass fraction, 푀퐹푏푎푡푡푒푟푦 , is used 푑푒푠푐푒푛푑,푉푇푂퐿 for the descending part of the mission, 푀퐹푏푎푡푡푒푟푦 . The final battery mass fraction is simply the sum of the components.

푙표푖푡푒푟 푟푎푛푔푒 푐푙푖푚푏,퐹푊 푐푙푖푚푏,푉푇푂퐿 푀퐹푏푎푡푡푒푟푦 = 푀퐹푏푎푡푡 + 푀퐹푏푎푡푡 + 푀퐹푏푎푡푡 + 푀퐹푏푎푡푡 ℎ표푣푒푟 푑푒푠푐푒푛푑,푉푇푂퐿 +푀퐹푏푎푡푡 + 푀퐹푏푎푡푡 (2.44)

2.13 TOTAL MASS CALCULATION The takeoff mass of the UAV is the sum of the components, which is defined as

푀푇푂 = 푀푒푚푝푡푦 + 푀푒푛푒푟푔푦 + 푀푝푎푦푙표푎푑 (2.45) Furthermore, the empty and energy components are defined as follows 퐹푊 푀푒푚푝푡푦 = 푀푠푡푟푢푐푡푢푟푒 + 푀푠푢푏푠푦푠푡푒푚푠 + 푀푎푣푖표푛푖푐푠 + 푀푝푟표푝푢푙푠푖표푛 푉푇푂퐿 +푀푝푟표푝푢푙푠푖표푛 (2.46)

푀푒푛푒푟푔푦 = 푀푏푎푡푡푒푟푦 (2.47)

In the empty weight category, the subsystems, avionics, and payload typically remain fixed. The propulsion, battery, and structure will depend on the mission and will iterate within the sizing. For preliminary estimation purposes, it can be convenient to display the weight in terms of the mass fractions. Equation 2.45 can be rearranged as follows

퐹푊 푉푇푂퐿 푀푝푟표푝푢푙푠𝑖표푛+푀푝푟표푝푢푙푠𝑖표푛+푀푝푎푦푙표푎푑 푀푇푂 = (2.48) 1−(푀퐹푏푎푡푡푒푟푦+푀퐹푠푡푟푢푐푡푢푟푒+푀퐹푠푢푏푠푦푠푡푒푚푠+푀퐹푎푣𝑖표푛𝑖푐푠) Gundlach [23] and Tyan et al. [6] recommend values for the mass fraction of the structure, subsystems, and avionics. Reasonable estimates for the structure mass fraction of FW aircraft are between 25-35%. This estimate should remain high, since the UAV will require additional structural support for the motor-tilting capability. Typical avionics mass fraction is around 5%. The subsystem mass fraction depends on the aircraft type. Advance surveillance aircraft can have a subsystem mass fraction of up to 15%. Aircraft with small cameras for real-time monitoring will typically have a subsystem mass fraction of 5-7%. In addition, the payload weight typically remains fixed because the customer defines it. Finally, the sizing estimation will require an initial guess for the takeoff mass 푀푇푂 . The solution for the sizing is found by iterating on the takeoff mass until a reasonably small value is achieved. The mass fraction estimates to be used in the sizing are 0.05, 0.07, and 0.30 for the avionics, subsystems, and structure.

2.14 SIZING RESULTS 2.14.1 Design Choices Before analyzing the constraint diagram, it should be noted that the designer must choose important vehicle parameters and configuration. The tri-rotor configuration is selected, in which all three propellers operate during VTOL mode. The front two propellers will tilt during FW flight while the third rear propeller becomes inactive. Initially, it is planned to have a two-blade propeller since they are common and easily accessible. For this UAV, the chosen parameters include the FW rate-of-climb of 2 m/s, the VTOL rate-of-climb of 2 m/s, the stall speed of 13 m/s, the maximum cruise speed of 17 m/s. Per Roskam [25], the clean max lift coefficient for a twin-engine propeller aircraft is 1.2; for this configuration, a max lift coefficient of 1.0 is used to account for the inefficiencies caused by the VTOL configuration. The max lift coefficient becomes important when the aircraft

36 begins to transition into/out of FW flight. In addition, the max lift coefficient can limit the choice of wing loading in the constraint diagram. The aerodynamic parameters include the aspect ratio 퐴푅, Oswald efficiency factor 푒, minimum drag coefficient 퐶 , loiter lift coefficient 퐶 , and best cruise lift-to-drag ratio 퐷0 퐿푙표푖푡푒푟

(퐿⁄퐷)푚푎푥. Table 2.5 shows the selected aerodynamic parameters.

Table 2.5. Aerodynamic Parameters for Preliminary Sizing 푨푹 5 풆 0.65 0.060 푪푫ퟎ 푪푳풍풐풊풕풆풓 0.5 (푳⁄푫)풎풂풙 10

There are methods to optimize the aspect ratio. For this preliminary analysis, historical data of VTOL vehicles is used to choose an aspect ratio of 5. A smaller aspect ratio requires less spanwise support, which ultimately leads to less structural weight. The small aspect ratio will also simplify the wing building process. A good preliminary estimate for Oswald efficiency factor is in the range 0.65-0.72 [23]. The typical range of minimum drag coefficients for a turboprop aircraft is 0.025-0.035 [22]. For this UAV, a value of 0.035 is used for the initial estimation of the minimum drag coefficient. The preliminary loiter lift coefficient can initially be assumed to be the 3D wing lift coefficient at 0° angle of attack. As the UAV design converges, the actual aircraft lift coefficient in level flight can be used. The best lift-to-drag ratio can be obtained using a rough estimate for propeller-driven aircraft. Roskam [25] presents a method for estimating the best lift-to-drag ratio for a fixed wing aircraft, as shown in Figure 2.19.

The area ratio 푆푤푒푡/푆푟푒푓 is estimated using Figure 2.20.

2.14.2 Constraint Analysis Results In developing the constraint diagram, iterating on the design of the vehicle will eventually converge on a final design. The final sizing constraint for the VTOL-FW UAV is shown in Figure 2.21.

Figure 2.19. Maximum lift-to-drag ratio trends. Source: [21] Raymer, D., Aircraft Design: A Conceptual Approach, Institute of Aeronautics and Astronautics, Washington, DC, 1992.

Figure 2.20. Wetted area ratios. Source: [21] Raymer, D., Aircraft Design: A Conceptual Approach, Institute of Aeronautics and Astronautics, Washington, DC, 1992.

Figure 2.21. Constraint diagram for final VTOL-FW UAV design.

The constraint diagram presents two choices for the wing loading – either 55 N/m2 or 100 N/m2. Both these options represent viable solutions to the mission. The 55 N/m2 wing loading implies a larger wing that allows the stall speed to be much lower. However, this wing is 23% heavier than the 100 N/m2 wing loading because it requires more structural support. The 100 N/m2 wing loading yields a wing area of 0.1718 m2 and a final weight of 1.762 kg.

The power required for VTOL climb is a function of the thrust multiplier factor 푇푀퐹 .

Increasing the thrust multiplier 푇푀퐹 increases the rate of climb of the UAV, but it also increases the total weight. Ideally, the UAV has a separate set of propellers for VTOL and FW modes. This allows the designer to optimize the propellers and ultimately increase the efficiency to decrease the required battery capacity. To simplify the VTOL system, this UAV has the same propulsion system for both VTOL and FW flight. The results for the weight estimation are shown in Table 2.6. Note that the weight of the vehicle is small enough for the electronics to remain relatively expensive. The wing and power requirements are shown in Table 2.7.

Table 2.6. Weight Estimation Results Payload 0 kg Avionics 0.088 kg Subsystems 0.123 kg Structure 0.526 kg Propulsion 0.705 kg Battery 0.320 kg Total 1.762 kg

Table 2.7. Wing and Propulsion Results Wing Area, 푺 0.1718 m2 Wing Chord, 풄 0.1854 m Thrust Required, 푻풓풆풒 2.059 kg

The sizing results from the constraint diagram will define the wing planform and powerplant. From the propeller disk loading relationship, the UAV’s propeller diameter is 0.3048 meters (12 inches). Typically, the motor and propeller must be matched to achieve top efficiency at the design point. For this UAV, the thrust required to meet the required climb rate is 0.686 kg. A pre-matched propeller-motor combination was found with a set of 0.254 m (10 inch) propellers and 935KV motors that produced 0.85 kg per motor. The wing area for the propeller is 0.1718 m2, which means that the chord length is 0.1854 m (7.3 inches) since the aspect ratio is 5.

2.15 HORIZONTAL TAIL SIZING Once the wing planform has been established, the horizontal tail can be sized. The horizontal tail can be calculated using the volume coefficient method [26], 푆 ℓ 푉 = 퐻푇 퐻푇 (2.49) 퐻푇 푆푐 where S is the wing area, c is the wing chord, 푆퐻푇 is the horizontal tail area, and ℓ퐻푇 is the distance from the CG to the horizontal tail’s aerodynamic center. For rapid prototyping in thin, symmetric airfoils, the aerodynamic center is assumed to be at the quarter chord. There are two physical constraints that guide the horizontal tail sizing. The first is the clearance required for the rear propeller, and the second is the lateral clearance of the pods. An initial preliminary estimation yielded a chord length of 5.08 cm and a span of 40.64 cm. This

40 preliminary design allows for initial stability estimations using VSAERO. The lift-induced forces and moments obtained from VSAERO provide a longitudinal stability analysis of the air vehicle. Figure 2.13 shows an example of the VSAERO geometrical definition. Figure 2.22 shows the fuselage/horizontal tail pressure profiles at the lateral centerline, and Figure 2.23 shows the wing/horizontal-tail pressure profiles at 푦 = 0.11 ∗ 푐.

Figure 2.22. VSAERO output pressure distribution over fuselage and horizontal tail.

Figure 2.24 shows how the original preliminary design produces a slightly unstable airplane in forward flight because the slope of 훿퐶푀/훿훼 is positive. Positive slope 훿퐶푀/훿훼 indicate that the air vehicle is unstable because moment increases as the angle of attack increases. A constraint diagram is developed for the horizontal tail. The three variable parameters for the horizontal tail are the moment arm ℓ퐻푇, the volume tail ratio 푉퐻푇, and chord 푐퐻푇. In addition, the two constraints in choosing a horizontal tail include the suggested range of volume tail ratios [26] and the required clearance for the rear propeller. Typical volume tail ratios are in the range of 0.3 and 0.6 [26]. Figure 2.25 shows the allowable design space for the horizontal tail.

Figure 2.23. VSAERO output pressure distribution over wing and horizontal tail.

Figure 2.24. Moment coefficient, 푪푴풀, for the initial design of horizontal tail. The center of gravity is assumed at the wing’s quarter chord location.

Figure 2.25. Constraint diagram for the horizontal tail. Left constraint is for propeller clearance, bottom curve constraint is for 푽푯푻 of 0.3, and top curve constraint is for 푽푯푻 of 0.6. CG is assumed to be at the wing quarter chord.

After choosing new horizontal tail parameters and verifying that the tail is within the design space, the longitudinal stability of the vehicle can be determined using VSAERO. The iteration is completed until a stable design is achieved. From Figure 2.25, it is visible that the 7.62 cm (3 inch) chord is within the allowable design space and produces a horizontal volume tail coefficient of 0.42. Figure 2.26 shows how the 퐶푀 − 훼 curve of the final design compares to the previous iterations. Figure 2.26 shows that both the second and final tail configurations have a zero moment near -5˚. Ideally, the zero-moment coefficient should be at 0˚ angle-of-attack. A further analysis of the lift versus moment coefficient is shown in Figure 2.27.

Figure 2.27 shows how the first design has a negative moment coefficient 퐶푀푌 at every lift coefficient. This behavior implies that the aircraft tendency would be to dive any given 퐶퐿. However, the final configuration appears to have the zero-moment location at the zero-lift point. Ideally, the aircraft has the required 퐶퐿,푐푟푢푖푠푒 at the zero-moment location so that the air vehicle can cruise at a zero-degree angle-of-attack. An analysis of the trim required for level flight is shown in Figure 2.28.

Figure 2.26. Impact of horizontal stabilizer placement on longitudinal moment coefficient, 푪푴풀, for two different longitudinal distances. The center of gravity is assumed at the wing’s quarter chord location.

Figure 2.27. Variation of lift versus moment for 3 different tail configurations. CG is assumed at wing quarter chord.

Figure 2.28. Effect of elevator trim on the 푪푴풀 vs 푪푳 curve for UAV.

The decision was made to have the entire elevator deflect during pitch control, which means that much less elevator deflection would be required to achieve higher pitching rates. In addition, the actual build process is simplified because the elevator will be both attached, and hinged, at the same location.

2.16 VERTICAL TAIL SIZING The primary role of vertical tails is to provide a form of yaw dampening. The first step in sizing the vertical tail is to determine the geometrical dimensions. This can be done using the tail volume coefficient method, which uses historical values from existing aircraft that are known to have good stability and control characteristics. The range of values for the volume tail coefficients [26] are

푉푉푇 = [0.02 … 0.05] where the rearranged volume tail coefficient equation is

푉푉푇푆푏 푆푉푇 = (2.50) ℓ푉푇 Because the horizontal tail location has been established, a rough estimate of the vertical tail moment arm, ℓ푉푇, can be chosen. Since the wing area, S, and span, b, are known,

45 the vertical tail area is then calculated using the equation above. For conventional aircraft, the vertical tail aspect ratio, 퐴푅푉푇, of 1.3 to 2 is typical [21]. The vertical tail aspect ratio is defined as

2 ℎ푉푇 퐴푅푉푇 = (2.51) 푆푉푇 where ℎ푉푇 is the height of the vertical tail. The height of the vertical tail can then be calculated by choosing the desired vertical tail aspect ratio. However, the aircraft configuration facilitates the build of two symmetrical rudders, as opposed to one tail at the spanwise centerline. The height of each vertical tail is found using

ℎ푉푇 = √퐴푅푉푇(푆푉푇/2) (2.52)

Typical taper ratios of the vertical tail, λ푉푇, range between 0.3 and 0.6 [21]. The taper ratio is defined as

푐푡𝑖푝,푉푇 λVT = (2.53) 푐푟표표푡,푉푇 The equation above, along with the area of a trapezoid, can be used to find an equation for one of the two vertical tail root chords.

푆 (푐 +푐 ) 푐 (1+λ ) 푉푇 = 푟표표푡,푉푇 푡𝑖푝,푉푇 ℎ = 푟표표푡,푉푇 VT ℎ 2 2 푉푇 2 푉푇

푆푉푇 푐푟표표푡,푉푇 = (2.54) ℎ푉푇(1+λ푉푇)

Because the vertical tail taper ratio λ푉푇 is known, the vertical tail planform is now known. To find the longitudinal location of the front edge of the vertical tail, the mean ̅ aerodynamic chord 푐̅ and spanwise location of the m.a.c., 푌푉푇 , can be found using Raymer [21].

2 2 (1+λ푉푇+λ푉푇) 푐푉푇̅ = 푐푟표표푡,푉푇 (2.55) 3 (1+λ푉푇)

ℎ푉푇 (1+2λVT) 푌̅푉푇 = (2.56) 6 (1+λ푉푇)

For simplicity, the trailing edge sweep Λ 푇퐸,푉푇 will be kept at zero, so the leading- edge sweep Λ퐿퐸,푉푇 of the vertical tail is defined by the taper ratio. The location of front edge of the vertical tail is now found using 푐̅ ℓ = ℓ − (푐 − 푐̅ ) + 푉푇 (2.57) 푉푇,푓푟표푛푡 푉푇 푟표표푡,푉푇 푉푇 4

Figure 2.29. Mean aerodynamic chord of a tapered wing. Source: [21] Raymer, D., Aircraft Design: A Conceptual Approach, Institute of Aeronautics and Astronautics, Washington, DC, 1992.

Per Roskam [27], the rudder is about 90%–100% of the vertical tail span, 25%–40% of the mean aerodynamic chord, and has a maximum deflection of 25˚-35˚. To have maximum rudder control, and because the effects of vertical tail centerline offsetting were not considered, the maximum values will be taken as the inputs for the vertical tail.

ℎ푟푢푑푑푒푟 = ℎ푉푇

푐푟푢푑푑푒푟 = 0.4푐푉푇̅ The values in Tables 2.8 and 2.9 show the inputs and outputs for the tail sizing.

Table 2.8. Input Values for the Vertical Tail Sizing Inputs ℓ푉푇 60.64 cm 푉푉푇 0.5 퐴푅푉푇 1.65 λ푉푇 0.6

Table 2.9. Output Values for the Vertical Tail Sizing Outputs 2 푆푉푇 148.84 cm (Total) ℎ푉푇 11.08 cm 푐푟표표푡,푉푇 8.395 cm 푐푡푖푝,푉푇 5.037 cm 푌̅푉푇 2.539 cm 푐푉푇̅ 6.856 cm ℓ푉푇,푓푟표푛푡 60.81 cm ℎ푟푢푑푑푒푟 11.08 cm 푐푟푢푑푑푒푟 2.742 cm Note: The output values, less the tail area, are for each individual vertical tail.

Figure 2.30. Planform view for one of the two vertical stabilizers.

CHAPTER 3

BUILDING THE PROTOTYPE

3.1 ELECTRONIC COMPONENT SELECTION VTOL-FW UAVs must perform in two different flight regimes and have the ability to transition between each mode. A flight controller must be selected to provide appropriate control. The first option is to use an Arduino board and develop the code for a VTOL-FW UAV. However, software development is beyond the scope of this project. The second, and most viable option is to use an off-the-shelf flight controller along with existing software that allows VTOL-FW transitions. The selected board is a KK2.1.5 Multi-Rotor Flight Control board, as shown in Figure 3.1, and the selected software is OpenAeroVTOL. This combination is chosen because the software OpenAeroVTOL is developed specifically for the KK2.1.5 board.

Figure 3.1. KK2.1.5 multi-rotor flight control board.

The KK2.1.5 board is equipped with an ATmega644 PA microcontroller and an MPU-6050 Six-Axis (Gyro + Accelerometer) Microelectromechanical system (MEMS) Motion Tracking Device. As an off-the-shelf component, the board only has preset multi-

49 rotor models and does not allow a VTOL-FW UAV configuration. OpenAeroVTOL, which can be flashed onto the board, is an open source software that allows the designer to define two flight modes (i.e. Tri-copter and Aircraft modes) along with the transition point between the two. The major tradeoff of the current setup is that the KK2.1.5 flight control board does not allow the operator to record accelerometer and gyroscope raw data. Another flight control board, which does allow recording of raw accelerometer and gyroscope values, can be installed for use in FW flight only. Once the board is selected, the other remaining electronics can be finalized. As previously mentioned, the motor-propeller combination includes a 10x4.5 propeller and a 935 KV motor. The rated thrust on this combination is 0.85 kg which is more than the required thrust. As flight testing progressed, another larger APC 11x5.5 propeller is swapped for the smaller 10x4.5 propeller to increase the thrust. Once the motor and propeller have been finalized, the electronic speed controller (ESC) must be selected such that the Amp rating is not exceeded by the propeller at full power. The current propeller is estimated to absorb around 10 Amps, which means that that a 12 Amp ESC is sufficient. However, the future aim of the project is to replace the open propellers with electric ducted fans (EDF). A 65mm EDF would provide adequate thrust-to-weight for the UAV. However, the EDF requires a 30 Amp ESC and for this reason the selected ESC’s are rated at 30 Amps. The only major tradeoff in having an ESC with higher amp rating is that the weight increases. Other electronics include eight servos for control authority; 2 for the front tilting motors, 1 for the yaw control in VTOL mode, 2 for the wing ailerons, 2 for the vertical tail rudders, and 1 for the horizontal tail. In addition, a small power distribution board was incorporated to facilitate power distribution. The next major electrical components are the Radio devices to communicate with the flight control board. The available transmitter for this project is a FrSKY Taranis X9D Plus 16-Channel 2.4 GHz ACCST, as shown in Figure 3.2. The radio transmitter transmits data at 2.4 GHz to a receiver that is installed onboard the UAV. A FrSKY X8R receiver is selected since the Taranis X9D transmitter is only compatible with FrSKY receivers. This X8R receiver has the capability of handling the 10 outputs channels required for this UAV.

Figure 3.2. Radio transmitter (left) and receiver (right).

The signal used for this project is a combination of SBUS and PWM. The transition servos are controlled with PWM and the rest of the outputs are controlled with SBUS. The final configuration of the electronic system is shown in Figure 3.3.

Figure 3.3. Final configuration of electric system for VTOL-FW flight capability.

Telemetry can be recorded via the receiver’s SmartPort at a max rate of 10 Hz. FrSKY has brand-specific sensors that allows onboard flight data acquisition. The sensors used for this project are shown in Figure 3.4 and listed in Table 3.1.

Figure 3.4. Electronic system bench testing (left) and batteries (right).

Table 3.1. FrSKY Sensors Onboard UAV FrSky FAS-40S Current Sensor FrSky SP-RPM - RPM and Dual Temperature Sensor FrSky FLVSS LiPo Voltage Sensor FrSky GPS V2 Sensor FrSky ASS-100 Air Speed Sensor

From Equation 2.1, it can be predicted that the required 3-cell battery mass of 0.320 kg corresponds to a 4050 mAh capacity requirement. Due to the availability of the batteries, an initial smaller LiPo battery was used during the initial tests. This battery has a 2200 mAh capacity with a nominal voltage of 11.1 Volts. A smaller 3-cell LiPo battery does not compromise performance of the propulsion system but it does shorten the UAV flight time. For initial testing, the smaller 2200 mAh battery is desirable because of the lower weight. The larger, more capable battery that was purchased is 3700 mAh with a nominal voltage of 11.1 Volts. The weight of these batteries is 190 grams for 2200 mAh and 297 grams for 3700 mAh. Figure 3.4 shows an example of the bench-testing of the electronics system setup.

3.2 FINAL VEHICLE PROTOTYPE LAYOUT The final VTOL-FW UAV design is shown in Figure 3.5. Figure 3.6 also shows the top-view dimensions of the UAV, in mm. The design in Figure 3.5 is a result of fast-prototype building techniques. Of course, the design can be streamlined by employing advanced manufacturing techniques with lightweight materials that can ultimately reduce drag and extend battery life.

3.3 MATERIALS AND PROTOTYPING TECHNIQUES Weight and cost were the driving factors in choosing the materials for the UAV. It was decided that additive manufacturing (a.k.a. 3D printing) could be employed for building the wing. Initially, seven airfoil ribs were printed for the wing. For the final iteration, the rib design is modified and the number of ribs is reduced to five to decrease weight. As shown in Figure 3.7, a balsa wood spar connects the ribs together. Figure 3.8 shows the final design for the airfoil wing ribs. A low-cost foam board is then wrapped around the airfoil ribs to form the wing. This allows the wing to have the desired airfoil shape without having extra material that full-foam wings typically do. To increase the spanwise structural integrity of the wing, packing tape is wrapped around the wing on the foamboard skin. The tape is relatively light weight and significantly increases the spanwise loading capability of the wing. Building the fuselage is facilitated by the foam-cutting machine available at San Diego State University. The cross-section of the fuselage, as shown in Figure 3.9, is designed in SolidWorks and uploaded to the SDSU foam-cutting machine. The fuselage is also wrapped in packing tape to reinforce the foam structure. A single balsa wood spar, attached to the rear part of the fuselage, is the structural support for the rear motor and servo. The main purpose of the wing-mounted pods is to not only house the electronics, but to provide strong structural support for the front two motors, horizontal stabilizer, and the two vertical stabilizers. An initial wing pod was built with foam board, but it didn’t provide the structural support required by the strong lifting forces on the UAV. The decision is made to switch to balsa wood because of its low weight and structural integrity for a UAV of the current size. The final shape of the wing-mounted pods is a square with 38.1mm (1.5 inches) outer sides.

Figure 3.5. UAV layout and configuration.

Figure 3.6. Top-view dimensions of VTOL-FW UAV, in mm.

Figure 3.7. Example of the wing rib and spar installation.

Figure 3.8. Final wing rib design ready to be printed.

Figure 3.9. Cross-section of fuselage.

Dimensions for the horizontal tail can be found in section 2.15. Both the horizontal and vertical stabilizers are made from foam. The entire horizontal stabilizer is hinged at the quarter-chord so that the entire surface provides elevator control. The vertical stabilizers are simply glued to the structure and their rudders provide control via tape-hinged attachments. The components required for tilting motors/propellers in any VTOL-FW UAV can quickly increase the structural complexity. In the case of this UAV, the tilting mechanism for the front rotors was developed using additive manufacturing. To reduce the complexity of the tilting mechanism, the servo was connected directly to the thrust axis of the propeller, as shown in Figure 3.10.

Figure 3.10. Tilting mechanism for front propulsion assembly.

The 3D printed servo casing (shown in blue in Figure 3.10) that holds the front tilting servo is simply glued to the balsa wood pod. The servo casing protects the servo from potential damage during an accident. This servo is attached to a 3D printed motor mount

(shown in green in Figure 3.10) that tilts for VTOL or FW flight. Future iterations can potentially include gears, or linkages, to avoid having the propeller vibration transmitted directed to the servo’s rotation axis. Similar to the front motor tilt mechanism, the rear motor/propeller installation is created using additive manufacturing with a similar design layout as shown in Figure 3.11. Since this vehicle is a tri-copter, the purpose of the servo from Figure 3.11 is to correct the inherent yaw instability created by the asymmetry in the UAV’s rear propeller. Initially the design provided good hover stability but as flight testing progressed, multiple issues became apparent. One issue is that the rear propeller’s vibration created an unstable response from the flight control board. In addition, the initial design of from Figure 3.11 amplifies the moment created by the propeller thrust vector during the servo’s stability corrections in hover. Propeller vibrations eventually led the balsa wood spar to fatigue. The solution to these issues was to redesign the tilting mechanism and to increase the size of the balsa wood spar.

Figure 3.11. First iteration of rear motor mount (left) and actual final design (right).

3.4. ACCURACY OF FINAL UAV WEIGHT There are two different configurations for this UAV. Configuration 1 uses the 3700 mAh battery with a total weight of 1.704 kg, while Configuration 2 uses the 2200 mAh

57 battery with a total weight of 1.597 kg. The sizing estimate for this UAV is 1.762 kg with a 4050 mAh battery that weights 0.320 kg. Configuration 1 has a slightly lower battery capacity of 3700 mAh and weights 23 grams less than the predicted battery weight. The final weight buildup is split the following groups: payload, avionics, subsystems, structure, propulsion, and battery. The final weight buildup for the UAV is shown in Figure 3.12.

Figure 3.12. UAV weight buildup.

The weight buildup shows good fidelity on the estimations for each component. Note that the UAV is not sized to carry payloads since the total vehicle weight increases exponentially with increasing payload weight. The avionics and subsystems mass fractions were only slightly higher than the sizing estimations. Good estimations for these groups appears to be around 8%. The structure mass fractions are under-estimating the actual weight. A good mass fraction estimate for the structure is 30%-40%; in this case, 35% is a good estimate for the structure mass fraction. The propulsion and battery mass estimation methods proved effective in determining almost identical mass fractions of around 40% and 18%, respectively. To recall, the avionics, subsystems and structure mass fractions are estimated empirically, while the sizing programs determines the propulsion and battery mass fractions.

CHAPTER 4

PROPELLER WIND TUNNEL TESTING

4.1 THE WIND TUNNEL Ideally, the wind tunnel can be used to map the transition regime of the propeller. The initial 25.4 cm (10 inch) propeller was tested in the San Diego Wind Tunnel. The wind tunnel test cross section is shown in Figures 4.1 and 4.2.

Figure 4.1. ISO-view of San Diego State University Wind Tunnel test section.

Figure 4.2. San Diego State University Wind Tunnel test section dimensions.

The wind tunnel has a water manometer that displays the change in water height as the wind velocity increases. For the pitot tube in the wind tunnel freestream air, the total pressures upstream (1) and at the pitot tube (2) are equal. Assuming steady, incompressible, and inviscid flow, Bernoulli’s equation can be applied from the freestream velocity. The initial velocity and the height terms are neglected.

𝑃̅표1 = 𝑃̅02 1 1 𝑃̅ + 휌 푉2 + 휌 푔ℎ = 𝑃̅ + 휌 푉2 + 휌 푔ℎ 푠1 2 푎푖푟 1 푎푖푟 1 푠2 2 푎푖푟 2 푎푖푟 2 1 𝑃̅ − 𝑃̅ = 휌 푉2 푠1 푠2 2 푎푖푟 2 For the balance in the manometer, the velocities are neglected, so the change in pressure is ̅ ̅ ( ) 𝑃푠1 − 𝑃푠2 = 휌퐻2푂푔 ℎ2 − ℎ1 Setting two equations above equal, the velocity can be related to the manometer’s change in water height.

2휌 푔(ℎ −ℎ ) 푉 = √ 퐻2푂 2 1 (4.1) 휌푎𝑖푟

4.2 EXPERIMENTAL SETUP A propeller stand was created to hold the electric motor and propeller inside the wind tunnel, as shown in Figure 4.3. The propeller stand allows for the motor wires to be concealed within the circular pipe. It is designed so that the propeller, motor, and load cell are in line with the thrust vector.

Figure 4.3. Propeller stand for installation in the wind tunnel.

The ATI Mini45 load cell, shown in Figure 4.4, records the forces and torques on all axes. The z-direction being the direction of the thrust vector. The load cell is connected to a DAQ system that records test data. Note that the load cell uncertainty values are measuring at 95% confidence levels. The uncertainty in the load cell, as shown in Table 4.1, is high compared to this project’s range of thrust measurements. However, the load cell both simplifies installation inside the wind tunnel and is readily accessible for use at the San Diego State University wind tunnel.

Figure 4.4. ATI Mini45-E Force and Moment Load cell.

Table 4.1. ATI Mini45-E Measurement Uncertainty Full-Scale Load [kg] Measurement Measurement Uncertainty [%] Uncertainty [kg] Fx 54.431 1.50 0.816 Fy 54.431 1.25 0.680 Fz 108.86 1.00 1.089 Tx 72.575 1.25 0.907 Ty 72.575 1.75 1.270 Tz 72.575 1.00 0.726

The propeller’s transition angle was simulated using the variable balance beneath the wind tunnel. Figure 4.5 shows the actual setup during transition testing inside the wind tunnel. The definition of the propeller axes is shown in Figure 4.6.

Figure 4.5. Actual propeller setup inside the wind tunnel.

Figure 4.6. Top view of propeller setup in wind tunnel.

4.3 STATIC TESTING Static thrust measurements of the propeller, prior to flight testing, will yield the thrust-to-weight of the UAV in VTOL mode. It also allows the designer to both verify the manufacturer’s thrust specification and to map the RPM to the propeller thrust. The initial

10x4.5 propeller was tested at 25%, 50%, 75%, and 100% throttle signal and the results are shown in Figure 4.7.

Figure 4.7. Static thrust test results for 10x4.5 propeller.

From Figure 4.7 it is clear that the thrust increases exponentially with RPM, which is expected [28]. The polynomial curve for this propeller is 푇 = 1.4415푥10−5 ∗ 푅𝑃푀2 − 0.0377 ∗ 푅𝑃푀 + 60.4441, where the thrust is in grams. The propeller appears to provide, best case, around 0.65 kg thrust at full throttle. The same battery is used to run the five static tests. There is a difference of 100 grams in max thrust as the battery voltage depletes, as seen in tests 1 and 5 in Figure 4.7. The motor is rated at 935 Kv and the battery is rated at 11.1 nominal Volts, so the motor should operate at 10380 RPM. Note how the actual RPM is much lower than the rated max motor RPM, which is a result of propeller loading since the motor was tested without a propeller and the RPM is close to the rated RPM. This test shows that the manufacturer overpredicts the thrust data for this propeller-motor-battery combination. Figure 4.8 shows the current draw from the motor. Similar to the thrust, the current also scales with the squared RPM. At each throttle signal (25%, 50%, 75%, and 100%), Figure 4.8 shows how the motor’s current draw remains

Figure 4.8. Motor current draw for 10x4.5 propeller during static testing. constant, regardless of the decrease in battery voltage. Figure 4.9 demonstrates a form of an important phenomena named voltage sag.

Figure 4.9. Available battery voltage for 10x4.5 propeller during static testing.

A fully charged 3S LiPo battery outputs 12.6 Volts, whereas a discharged battery is around 9.9 Volts. Figure 4.9 shows how the total battery voltage is slowly depleted after each test run. More importantly, the voltage sag becomes apparent as the RPM increases. Ideally, the voltage would remain constant to produce a constant RPM at any given throttle signal

(since motor RPM is proportional to battery voltage). However, as the throttle signal is increased, the propeller load creates a voltage sag that decreases the effective RPM (note how the max no-load motor RPM is 10379, but the max RPM with the propeller is less than 8000). For UAVs, the initial hover and climb part of the mission will typically have a fully charged battery, which means that the highest possible thrust is available. As the end of the mission is reached and the battery is depleted, the UAV must have enough thrust to properly descend in VTOL mode. If the 푇/푊 is close to 1, the battery might not have enough voltage to provide the required thrust for hover and descent. A careful consideration must be placed on the additional thrust required to control the pitch and roll in VTOL model. As the battery depletes, the voltage might drop enough such that there isn’t enough pitch and roll control to overcome instabilities caused by either the UAV design or outside forces like wind turbulence. Since the propeller power is simply the current times the voltage, the power can also be plotted as shown in Figure 4.10.

Figure 4.10. 10x4.5 propeller power consumption during static testing.

The sizing predicts an individual motor’s required thrust to be at minimum 0.587 kg in order to hover. From Figure 4.7, this thrust requirement is met at maximum throttle signal. However, the slight decrease in effective RPM with a low battery will hinder the UAV’s

65 hover stability. The sizing’s predicted power requirement is 66 Watts, but from Figure 4.10 the propeller is consuming 100-110 Watts. The propeller shows poor efficiency because, although it produces the required thrust, the power consumed is 67% higher than predicted. Ryan Aeronautical Company [29] presents the static thrust and power coefficients as 푇 퐶푇 = 2 4 (4.2) 휌푛 퐷푝 푃 퐶푃 = 3 5 (4.3) 휌푛 퐷푝 where 푛 is the revolutions per second, and 퐷푝 is the diameter. Furthermore, the Figure of merit (also known as the propeller efficiency) is defined as

3⁄2 퐶푇 휂푝 = 0.798 ∗ (4.4) 퐶푃 Incorporating these equations with the test results yields the thrust and power coefficients shown in Figure 4.11. A 10x5 thin electric APC propeller is shown to compare with our 10x4.5 propeller. The APC 10x5 propeller data is obtained from the UIUC propeller database, where the test data for hundreds of propellers has been made available. The two big differences between the APC and test propellers are the pitch and the material. Relatively speaking, APC propellers are much stiffer than the 10x4.5 propeller used during testing. The pitch of the APC propeller is 5 inches/revolution versus the 4.5 inches/revolution of the 10x4.5 propeller. The test propeller appears to have a much lower thrust coefficient than the APC propeller. In addition, the power coefficient indicates that the test propeller is consuming much more power. The efficiency is shown in Figure 4.12. These tests confirm that the test propeller’s efficiency is in fact poor. The next obvious step is to investigate other propulsive devices to compare to the 10x4.5 propeller.

4.3.1 Static Testing Propeller Comparison The 10x4.5 stock propeller that was included with the motor is used during the initial flight tests. However, another APC propeller with a larger 11-inch diameter is adopted and proves to provide much more thrust. The test results for the APC 11x5.5 propeller are shown in Figure 4.13. 66

Figure 4.11. Static thrust coefficient (left) and static power coefficient (right) for 10 inch propellers.

Figure 4.12. Propeller efficiencies.

Figure 4.13. Static thrust comparison of two propellers.

The 11-inch propeller provides almost 800 grams of thrust, compared to the 650 grams provided by the 10-inch propeller. The current draw and battery voltage supply is shown in Figure 4.14.

Figure 4.14. Static testing comparison of motor current draw and available battery voltage.

The 11-inch propeller obviously requires and additional 2 Amps of current. The voltage sag for the 11-inch propeller appears to follow the same trend seen in the 10-inch propeller. If the battery voltage range is between 12.6 Volts and 9.9 Volts, both propellers will cause the battery supply voltage to drop 25% of the total available voltage at max throttle. This information is crucial to determining the 푇/푊 ratio of the UAV because the

68 proper thrust must be available even if the battery is near depleted and operating at max throttle. The power required is shown in Figure 4.15.

Figure 4.15. Static testing comparison of propeller power consumption.

Increasing the propeller diameter from 10-inches to 11-inches will require about 38% more power and produce about 23% more thrust. This shows how the efficiency will be crucial in extending, or limiting, the UAV’s flight time. Furthermore, data is obtained from the UIUC propeller database to compare with the results obtained during static testing. The static thrust coefficients, static power coefficients, and efficiencies are shown in Figures 4.16 and 4.17.

Figure 4.16. Comparison of static thrust coefficients (left) and static power coefficients (right).

Figure 4.17. Comparison of propeller efficiencies.

The UIUC database static thrust results are fairly similar to the APC 11x5.5 propeller testing for this project. The major difference occurs in the static power coefficient. The large power coefficient discrepancy is then translated in a much lower efficiency, as shown in Figure 4.17. For a “large” thrust coefficient, the lowest possible power coefficient is desired to obtain a “high” efficiency. Since the power is measured between the battery and the system, it is possible that the low efficiency is a result of high inefficiencies in the electric motor and/or ESC. The next step, not covered in this test, is to measure the power after the ESC and before the motor to check if the ESC has an adverse effect on the efficiency. Another possibility is that the electric motor KV is not matched properly with the voltage. An incorrect combination would introduce high inefficiencies in the motor. The electric motor manufacturer gives a specified voltage range, but it is possible that the motor is not built to the given specifications.

4.3.2 Ducted Fan Consideration A 64mm electric ducted fan (EDF) was originally considered for a UAV upgrade, as shown in Figure 4.18. The EDF has 11 blades and is operated by a 3900 KV electric motor. The bench test results are shown in Figures 4.19 through 4.20. The specifications claim 900 grams of thrust, which means that the UAV 푇/푊 ratio would be 1.56. The APC 11x5.5 propeller provides a 푇/푊 of 1.56. However, the increase in 푇/푊 does not include the larger ESC required to provide a constant 55 Amps, the larger structural weight to accommodate the EDF, and the larger battery to compensate for the 70

Figure 4.18. 64mm electric ducted fan.

Figure 4.19. EDF thrust test results.

Figure 4.20. EDF voltage and current draw test results.

71 higher power consumption. With these considerations, keeping the APC 11x5.5 propeller appears to benefit the simplicity of the UAV.

4.4 WIND TUNNEL TRANSITION TESTING Transition testing of the propulsion system allows the designer to obtain experimental values for the lifting forces on the vehicle. Table 4.2 shows the three variables tested in the wind tunnel.

Table 4.2. Propeller Transition Test Plan Variables Propeller Wind Throttle Transition Angle Tunnel Signal [% [deg] Speed [m/s] throttle] 0 5 25 15 10 50 30 15 75 45 20 100 60 75 90

Figures 4.21 and 4.22 show the forces and torques obtained for the 10x4.5 propeller. The load cell moves with the propeller axis, so the z-force represents the propeller’s thrust vector. If the propeller angle-of-attack is ignored, then the thrust decreases with increasing wind speed. The static test shows a maximum propeller thrust around 640 g. At 5 m/s and 0°, the maximum thrust for the propeller drops to 550 g. As the wind speed increases to 15 m/s at 0°, the propeller thrust becomes zero. This leads to the conclusion that this propeller will not be able to independently accelerate the UAV past 15 m/s. The max velocity is close, but not quite meeting the 17 m/s max cruise velocity for the UAV. It is also important to note that the propeller was not tested above 10 m/s for angles higher than 60° because of visible and audible vibrations during the test. In addition, note how the propeller thrust force (z- direction) appears to reach its max static thrust during every test. Because the thrust force is only in the propeller axis, the lifting component of the force can be calculated using 퐿 = 퐹푧 sin(훼), and the results are shown in Figure 4.23. 72

Figure 4.21. Propeller forces during transition.

Figure 4.22. Propeller torques during transition.

Figure 4.23. Propeller lifting force component during transition.

During the transition from VTOL to FW, the propeller can maintain the vehicle level up to 75° and 5 m/s. After 60° and 5 m/s, the transition to FW flight must occur rapidly to minimize loss of altitude. The information provided by this test allows the designer to allocate appropriate intervals for the VTOL-FW transition, and vice versa. It is obvious that this propeller does not provide enough lift to avoid loss of altitude during the transition. A solution to this is to increase the 푇/푊 ratio of the UAV. The ratio used in the sizing is 1.1, which is obviously not sufficient to provide an adequate transition.

CHAPTER 5

FLIGHT TEST – HOVER

The following sequence of events will detail the multiple roadblocks in achieving stable hover conditions for this UAV with relatively low 푇/푊 ratio of 1.1.

5.1 INPUT PARAMETERS FOR OPENAEROVTOL After finalizing the geometrical dimensions of the UAV, the control board was programmed to define the state of each output (see Figure 3.3 for details on the electronic system layout). Figure 5.1 shows the OpenAeroVTOL settings for the tri-rotor UAV.

Figure 5.1. Inputs for OpenAeroVTOL.

The scope of this project does not encompass the development of a control system for this UAV. However, the software to control the UAV does require the user to define the

Proportional and Integral Values for the control system, as shown in Table 5.1. These values are experimental results obtained from testing various combinations until stable hover is achieved. Control values are not utilized during FW flight since the pilot will have full control authority. Note that these values are sensitive to the UAV geometry, mass distribution, and center of gravity.

Table 5.1. Required Input Proportional and Integral Gains for Control System Flight Flight Profile Profile 1 2 Roll P: 60 0 Roll I: 0 0 Roll I Limit: 0 0 Roll I Rate: 2 0 Roll AutoLvl: 10 0 Roll Trim: 0 0 Pitch P: 60 0 Pitch I: 0 0 Pitch I Limit: 0 0 Pitch I Rate: 2 0 Pitch AutoLvl: 10 0 Pitch Trim: 0 0 Yaw P: 20 0 Yaw I: 0 0 Yaw I Limit: 0 0 Yaw I Rate: 2 0 Yaw Trim: 0 0 Z-Axis P: 60 0 Z-Axis I: 0 0 Z-Axis I limit: 0 0

5.2 HOVER TEST DATA Multiple tests are conducted during hover. Results for the multiple hover tests are shown in Figure 5.2. Before jumping into the description of Figure 5.2, it should be noted that each test # represents an individual hover attempt. The different colored clusters represent separate test sessions.

Figure 5.2. Hover testing results.

A max power test is conducted with 10-inch propellers by constraining the UAV and using the full throttle setting. UAV’s takeoff weight is 1.713 kg and the max available thrust is as high as 1.95 kg and can drop as low as 1.620 kg when the battery is depleted. The initial propeller and motor combination do not provide adequate thrust during the final descent mission leg. The next step in solving the propulsion issue was to increase the propeller diameter. The new APC 11x5.5 propeller is tested with the small battery (2200 mAh). The new 11-inch propeller shows better hover control and a lower power requirement. The third test is when the UAV began displaying significant yaw instabilities that completely compromised the entire UAV stability in hover, therefore requiring more power to overcorrect the inherent instabilities. The fourth test session included two separate hover attempts. A successful first hover was done with a full battery and it lasted around 1 minute. The second hover attempt lasted five seconds, in which the combination of low-speed winds, lower battery voltage, and

78 propeller-induced vibrations led to a catastrophic crash. This event provided the opportunity to re-design several air vehicle components, which are presented in the section 5.4. The fifth test session was conducted with the redesigned UAV. The lower empty weight (no battery) of 1.407 kg in the new model, compared to the previous 1.523 kg model, proved to significantly decrease the power required for hover. Test session 5, along with 7 and 8, were also done to experiment with the P & I stability values. Carbon fiber material can significantly reduce the total propeller weight. In this case, the total propeller weight is decreased by 58% by simply replacing the composite APC 11x5.5 propellers with 11x5 carbon fiber propellers. A slightly higher power consumption in test session 6 indicates that the carbon fiber propellers are less efficient that their APC 11x5.5 propeller counterparts. The carbon fiber propellers did not have a tight-fit on the electric motor mount, which led to high vibrations. These vibrations did not allow the flight control board to correctly stabilize the UAV. In addition, the carbon fiber material was hollow, which prevented further manufacturing to adapt the propeller to the electric motor mount. Test session 9 includes the mission battery with a capacity of 3700 mAh. The total weight of 1.704 kg is on par with the sizing’s predicted values of 1.762 kg. Mean value for the power required for hover is 267 Watts. Note that the power required mean value for the 2200 mAh battery is 232 Watts since the total weight is 1.597 kg. Although the 2200 mAh battery configuration consumes less power, it also provides much less flight time. Test session 10 is conducted towards the end of the testing phase, when the APC 12- inch propellers become available for use. The APC 12x8 propellers are installed and tested with the 2200 mAh battery, with a total takeoff weight of 1.588 kg. Note that the takeoff weight is slightly lower, and it is because part of the air vehicle is rebuilt after having crashed during transition testing. The power consumption is higher than the 11-inch propellers, as expected. Interestingly, this configuration consumes less power than the 10-inch propellers at full-throttle. The UAV displays good hover stability with the same proportional and integral gains in the flight control board. Test session 11 is similar to test session 10, except that the 3700 mAh battery is installed and the total weight is 1.695 kg. This takeoff weight is almost identical to the weight from test session 9. Therefore, it is appropriate to compare the power consumption of

79 the test session 9 to test session 11. As expected, the larger 12-inch propeller draws more power than the 11-inch propeller. Energy consumption rate provides insight into whether the battery energy is sufficient for the hover mission leg. Figure 5.3 shows the energy consumption rates for the same test results from Figure 5.2.

Figure 5.3. Energy consumption rate for hover test results.

Note how after test session 4 (purple), the total vehicle weight is decreased and therefore the energy consumption rate drops significantly to 6 mAh/s. Test sessions 10 and 11 show a higher value of 7.28 mAh/s, which is expected because the 12-inch propeller requires a greater current and therefore greater electrical power. The heavier 3700 mAh battery configuration consumes slightly less energy than the 2200 mAh battery configuration. From the sizing predictions, the hover mission leg is estimated to consume 1.78 mAh/s. The reason for this large discrepancy can be investigated by studying the effects of the propeller diameter and efficiency on the energy consumption rate, as shown in Figure 5.4. The sizing estimation directly ties the propeller efficiency and the diameter to the energy required for hover. Lines for constant energy consumption rates for the sizing are

Figure 5.4. Rate of energy consumption for sizing and test results. shown above (in red). The propeller diameter and energy consumption rates can be used to find the propeller efficiency. Note that the propeller diameter from the sizing is 0.3048 meters (12 inches) but the propeller diameter used is only 0.2794 meters (11 inches). An inaccurately optimistic propeller efficiency of about 60% is chosen during the sizing prediction. The reason for the highly optimistic efficiency is because the regression model for the efficiency-thrust relation is used (see Figure 2.15). The actual propeller efficiency is closer to 20%. The 12-inch propeller displays a much lower efficiency for the same weight. Since the propeller obtained has a higher pitch, this means that it operates with higher efficiencies at greater speeds. Therefore, it is expected that the APC 12x8 propeller has a lower efficiency than the APC 11x5.5 propeller. The low efficiencies can be verified with JavaProp [30], a tool for the design and analysis of propellers. The JavaProp solution, shown in Figure 5.5, shows the results for an 0.2794 meter (11 inch) propeller with similar, but not exact, operating conditions in hover. Results in Figure 5.5 show that propeller efficiency of 28% is much lower than the regression model’s predicted value. A solution to this problem is to develop two sets of

Figure 5.5. JavaProp results for propeller in hover. propellers, each set being optimized for VTOL and FW flight. For propellers that will operate in both VTOL and FW flight, the efficiency in hover will be crucial to maximizing flight time. However, this “hybrid” propeller must also have the capability of operating at the required cruise speed.

5.3 INVESTIGATION OF VTOL DISK LOADING The UAV sizing uses an empirical disk loading regression model to determine the required propeller area. To recall, the disk loading is the ratio of required thrust to propeller area. The required propeller area ultimately provides the power required to operate in VTOL mode. Although Tyan et al. [6] regression model is geared towards quadcopters, previously shown in Figure 2.16, the regression model is applied to the tri-copter sizing. The reason being that, for the same weight, the model will simply predict a larger propeller in a tri-copter than in a quadcopter. A larger diameter is expected since the tri-copter will have to compensate for the extra propeller in the quadcopter. A survey is conducted of recently-built and developed tri-copters in the market, as shown in Figure 5.6.

Figure 5.6. Disk Loading regression models for tri-copters and quadcopters.

The tri-copter disk loading data from Figure 5.6 does not appear to scale with takeoff mass. The tri-copter regression model is 퐷퐿푡푟푖푐표푝푡푒푟 = 35.6178 ∗ 푀푇푂 + 154.6599, and the correlation coefficient is 0.2548. This model is plugged into the UAV sizing but the takeoff mass does not converge. As a comparison, Tyan’s original regression from Figure 2.16 is shown in Figure 5.6 (in red). The slope of Tyan’s regression model is increased until the slope of Equation 2.21 matches the required power from flight testing. The linear regression that matches the actual power is 퐷퐿푚표푑푖푓푖푒푑 = 8.8718푀푇푂 + 74.991. Note how the takeoff mass increases to 2.5, which is expected because the extra consumed power requires more battery weight, which in turn drives up the vehicle weight.

5.4 DESIGN MODIFICATIONS TO IMPROVE HOVER STABILITY After test number 4, it became apparent that the UAV required either a lower takeoff weight, or a higher thrust-to-weight ratio. Decreasing the weight of the vehicle is the first step in attempting to improve hover performance. The first step in reducing weight was to streamline the design of the 3D-printed wing ribs. The original rib design was bulkier and was printed with less cutouts. In the new

83 design, as previously shown in Figure 3.8, the wing ribs are thinner, have larger cutouts to remove more material, and are printed with less material infill. Originally, the width and height of the wing-mounted pods are 5.08 cm (2 inches) but are later decreased to 3.81 cm (1.5 inches). The size of the wing-mounted pods is decreased to the minimum size required to both house the electronics and provide support for the front tilting-motor assembly. Another overlooked problem in weight management is the weight of the wires. The ESC’s and electric motors are located at the air vehicle extremes, which means that the wire must run from the power distribution board, located in the fuselage, to the front and back of the air vehicle. After the first build and crash, the wire weight is streamlined to provide the minimum length required and maintain the lowest weight possible. The first iteration of the fuselage is simply cut-out with a hand saw. For the second iteration, a new fuselage is created using the hot-wire tools at SDSU. Streamlining the fuselage design allows the fuselage to maintain structural support with the minimum material possible. Original propeller sizing estimation is 12-inches, but a 10-inch propeller is chosen due to the manufacturer specifications claiming to meet the thrust requirement. After initial testing, the thrust specification is not met by the manufacturer, so a larger 11-inch APC propeller is purchased. The larger APC propellers are heavier and therefore have a higher inertia during operation. In hover mode, the larger propeller inertia appears to help damp the self-induced vibrations created by the propeller. For tri-copters, the two front propellers spin in opposite directions to counteract the torques. The rear propeller’s torque must be corrected using the servo that is controlled by the flight control board, as shown in Figure 5.7. After about five hover test sessions, the UAV’s flight control board became unable to correct the inherent tri-copter’s yaw instability.

Figure 5.7. Demonstration of yaw control in VTOL model.

The first issue with the yaw instability is that in trying to minimize weight, a lightweight balsa wood spar is installed to attach the rear motor to the fuselage. Over time, the torque created by the servo controlling the yaw started to wear the balsa wood spar until its structural integrity became compromised, as shown in Figure 5.8. The solution to this issue was to use basswood instead of balsa wood, and to increase the width of the spar. The length of the spar is short enough that the increase in weight from the higher density of basswood is small.

Figure 5.8. Balsa wood spar deflection leading to yaw instability.

The second issue with yaw instability is that the servo’s rotation axis is relatively high (see Figure 3.11 for reference). The red tilting mechanism shown in Figure 5.8 was redesigned to remove the additional moment created by the distance from the balsa wood spar to the servo’s axis of rotation. The redesigned yawing mechanism allows much better yaw control with minimal torque produced during a yaw maneuver. The third issue with yaw instability is that the propeller and motor vibrations were transmitted into the flight control board’s gyroscopes and accelerometers. More specifically, the flight control board gyroscopes are highly sensitive to vibrations because they detect and attempt to correct rotational motions. One solution was to soft-mount the motors onto the vehicle airframe. The purpose of soft-mounting is to damp the vibrations transmitted from the electric motor into the airframe. Electric tape was added in between the bottom of the electric motor and the support frame. In addition, electric tape was installed into the motor’s

85 screw mounting holes during the installation of the motor screws. These steps have been proven, by hobbyist, to help reduce vibration noise picked up by the accelerometers and gyroscopes. The other solution, and probably the most effective, was to create a vibration- damping mount for the flight control board as shown in Figure 5.9.

Figure 5.9. Vibration damper for flight control board.

This vibration damping mount is simply two 3D printed plates connected by four silicone vibration damping balls. After implementing the solutions presented above, the UAV displayed much better hover stability.

CHAPTER 6

FLIGHT TEST – FORWARD FLIGHT

Before transition testing, it is desired to find the FW flight performance of the UAV. VTOL-FW UAVs do not have the capability of landing like typical fixed-wing aircraft. To prove FW flight capability, the UAV is fitted with landing gear to assist during a takeoff and landing. The FW flight configuration, as shown in Figure 6.1, has four landing gear legs. Note that the UAV is tested with the APC 11x5.5 propellers.

Figure 6.1. UAV with fitted landing gears for FW flight testing.

For strong structural support and to avoid the front propellers from accidentally hitting the ground, the front two landing gears legs are constructed with rigid 3D printed studs and off-the-shelf tires. The rear two tires legs are constructed with flexible wire to both add shock absorption and minimize unnecessary weight. A softball field dirt patch with low ground resistance is chosen as the takeoff and landing area. Figure 6.2 shows the GPS data obtained for the FW flight test. During the FW flight test, the UAV is flown straight and level, where controlled turns allow the UAV to fly along the perimeter of the field. The front propellers are tilted up 5° to help the UAV during takeoff and landing. The adverse of effects of the fixed landing gear are the additional drag and weight. Table 6.1 shows the results for the FW flight test.

Figure 6.2. GPS data from FW flight test.

Table 6.1. Performance Results for FW Flight Results Sizing Prediction Ground Altitude 28.5 m (mean) 100 m Total Altitude 134 m 100 m Distance (cruise + loiter) 2160 meters 1920 meters Distance (cruise + N/A 2170 meters loiter+ climb) Velocity 14.9 m/s (mean) 17 m/s (max cruise) Power 171 Watts 131 Watts Energy Consumed 643 mAh 194 mAh Energy Consumption Rate 4.43 mAh/s 1.71 mAh/s Battery Capacity 2200 mAh 4050 mAh % Battery Consumed 29% for 2200 5% mAh 16% for 4050 mAh

The energy consumption rate for the UAV in FW mode appears to be 2.6 times higher than predicted, which means that battery capacity does not provide the required flight time. The power required for cruise is 171 Watts, or 31% higher than predicted. In calculating the cruise and loiter performance, it appears that optimistic values are used for the aerodynamic parameters, as shown in from Table 2.5. A possible explanation is that the non-streamlined components of the air vehicle contribute a higher parasite drag than estimated. First, the parasite drag of the wing-mounted pods can be reduced by changing cross- section from a square to circle. This would be possible with advanced manufacturing techniques. Second, the front tilting servos are partially outside of the wing-mounted pods (see Figure 3.10), which means that there will be higher drag. Third, and probably the highest contributor to drag, is the rear propeller assembly because it is inside the airstream during FW flight. For the rear open propeller, the best solution would be to align the propeller elevation to be in-line with the fuselage. This would eliminate the interaction of the propeller with the airstream in FW flight. A recently developed UAV software can be consulted to obtain an estimate of the aerodynamic characteristics of the UAV in FW mode. ComQuest Ventures’ Typhon UDX is a UAV design software that allows the design and performance analysis of electric air vehicles. This software is used to model both the geometry and electronic setup for the UAV, as shown in Figure 6.3.

Figure 6.3. Typhon UDX air vehicle design in FW mode.

After setting up the model and defining the electronic system, the total weight and center of gravity is matched to the actual air vehicle’s center of gravity. The student version allows the designer to simulate a built-in “wing airfoil.” The “wing airfoil” contains a slight amount of camber, but it does not perform exactly like the NACA 4415 airfoil. The aerodynamic characteristics, which are calculated within Typhon UDX using proprietary methods that have been verified through Computational Fluid Dynamics (CFD), are shown in Figures 6.4 and 6.5.

Figure 6.4. Typhon UDX lift and drag coefficients.

Figure 6.5. Typhon UDX lift-to-drag ratio.

As expected, the open-propeller creates an overwhelming amount of drag, which ultimately leads to less flight time. The software predicts a low lift coefficient at 0° angle-of- attack. The minimum drag is around 0.65, which is only slightly larger than the estimated values of 0.06. The poor lifting characteristics are translated to a low lift-to-drag ratio. This software, along with the actual flight test, suggest that advanced manufacturing techniques can better streamline the UAV profile, and ultimately provide longer flight times.

CHAPTER 7

FLIGHT TEST – TRANSITION TESTING

The aim of the first transition test is to prove VTOL-FW transition. The flight plan starts by hovering to 20 meters and quickly transitioning into FW mode. Note that this test is done with the APC 11x5.5 propellers. Figure 7.1 shows the progression of the initial VTOL- FW transition.

Figure 7.1. First test of VTOL to FW flight.

The transition from VTOL to FW flight causes a significant loss in altitude, which is expected from the wind tunnel results. The transition back from FW to VTOL mode is done relatively fast and close to the ground, leading to a pitch-up maneuver that destabilizes the air vehicle. The extremely low altitude of the UAV does not allow it to recover from the pitch- up and ultimately causes it to crash. Unfortunately, the flight data becomes corrupted, so the performance parameters cannot be analyzed.

After rebuilding the UAV again, the 12-inch propellers are tested in hover to check the vehicle stability. Once this is confirmed, the UAV climbs to 30 meters and then transitions into forward flight. Again, the purpose of this paper is not to optimize the controls, but to verify if the sizing methods can develop an operable UAV that can perform every mission leg. Figure 7.2 show snapshots during the UAV transition from FW flight to VTOL mode. The low resolution on the images below are because the UAV was cruising at 45 meters before transitioning to VTOL.

Figure 7.2. Progression of UAV transition from FW flight (left) to 45° motor-tilt transition (middle) to VTOL (right).

Although it is not clear in the images from Figure 7.2, the front motors in the middle picture are tilted at 45°. This configuration, with the APC 12x8 propeller and 3700 mAh battery, displayed a smooth FW-to-VTOL transition with almost no loss in altitude. With an integrated algorithm that provides optimal control, this UAV has the capability of performing proper transitions from VTOL to FW, and vice versa. The flight data for this test shows that the initial VTOL climb height is 20 meters. The transition to FW flight led to a 15-meter drop in altitude because the propellers are tilted VTOL to FW position very rapidly. The UAV climbed to around 45 meters to cruise. After about 70 seconds in FW flight, the propellers are tilted to 45° and then to VTOL mode in a rapid succession. The mean cruising speed for this UAV configuration is 15.8 m/s and the mean cruise power is 244 Watts. In the final mission leg, the UAV descends in VTOL mode. The pilot must be careful of descending rapidly and inducing Vortex Ring State (VRS). VRS occurs when an air vehicle has no forward speed and its rate-of-descent is too large. During hover, the propeller creates a downwash with a vortex, at the tip of the propeller, that will inevitably recirculate from the exit back into the inlet. If the air vehicle descents too fast, the propeller drops into

93 its own downwash that is recirculated into the propeller at an angle that will stall the propeller and ultimately lose lift. This phenomenon is seen in the UAV during rapid descents, in which VRS induces an oscillation in the UAV. The relatively large inertia of the vehicle does not allow the propellers to correct the oscillation, so the UAV descends rapidly but is still able to land safely.

CHAPTER 8

CONCLUSION

The sizing method presented in this paper contains empirical assumptions that demonstrate good accuracy in the results. To obtain good results, an interactive iteration must be performed between the UAV design parameters and final layout configuration. The final weight estimated for this project is 1.762 kg and the actual results are 1.704 kg. Additive manufacturing facilitates the development of complex components that are typical in hybrid UAVs, like the parts that attach the pods to the wing and wing to the fuselage. The availability of off-the-shelf components ultimately shortens the lead time on all the items for this project. The sizing estimation for the propeller is 12 inches, but a 10-inch propeller and 935 KV electric motor are initially chosen because the manufacturer claims to meet the thrust requirements. After flight and wind tunnel tests, the data show that the manufacturer’s specifications are not met since this propeller-motor combination provides a maximum ratio of 1.1 while the required ratio is 1.18. The vehicle is able to hover in minimal wind conditions, but as the voltage is depleted, the thrust-to-weight decreases and the motors do not have enough thrust allocated to provide stability correction in VTOL mode. Promising hover performance is shown with a new 11-inch propeller. This first prototype with the 11- inch propeller crashed after a few flights, but it provides the opportunity to re-design some structural components and ultimately decrease the empty weight (no battery) from 1.535 Kg to 1.407 kg. This 8% decrease in weight, along with other efforts aimed at minimizing vibrations, allow the UAV to perform well and be stable in VTOL mode. The next step is to test and prove FW flight exclusively. This test is successful and proves that the UAV cruises at about 15 m/s, which is near the 17 m/s sizing prediction. In addition, the UAV’s ground takeoff speed is around 9 m/s while the stall speed used for the sizing is 13 m/s. Finally, the UAV’s transition capabilities are tested with the 11-inch propeller configuration. The VTOL

95 to FW transition is successful but there is a substantial loss in altitude. The loss in altitude occurs for two reasons: the first being that the transition is not optimized since it’s done by a pilot, and the second is that it’s highly possible that the 11-inch propeller does not provide adequate lifting force while the UAV gains enough forward speed to have the wing develop its required lifting force. During the FW to VTOL transition, the combination of low altitude and a bad pilot transition led to an oscillation and then a crash. The UAV is then rebuilt and retrofitted with 12-inch propellers that had not been previously available. A final transition test proves the UAV’s capability to transition from VTOL to FW and back. The sizing shows that a large contributor to the battery weight is the VTOL mission leg. From flight testing, the energy consumption of an 11-inch propeller is around 6 mAh/s. The propeller efficiency regression model used in the sizing process estimates FW and VTOL propeller efficiencies around 55% and an energy consumption rate of 1.78 mAh/s. An integrated analysis of the energy consumption rate, propeller diameter, and propeller efficiency show that the actual propeller hover efficiency is closer to 20%. Since the off-the- shelf propellers are developed for FW flight aircraft, a low efficiency is expected during hover. Ideally, one set of propellers is optimized for VTOL and another set for FW flight. Optimistic values are selected for the aerodynamic parameters. These optimistic values don’t affect the UAV’s ability to perform the mission, but they do adversely affect its performance and therefore, shorten its flight time. The aerodynamics from VSAERO are modeled without the open propeller and wind-mounted pods. The full UAV design is implemented into Typhon UDX and the results show a higher drag and lower lift coefficient. For this mini UAV, the effects of the non-streamlined shape are evident in the larger energy consumption rate obtained from flight testing. Voltage sag is not considered during the sizing but becomes important in VTOL UAVs that have thrust-to-weight ratios close to 1. The propeller load creates a voltage sag in the battery’s supply voltage. At max RPM, static testing shows that the total available voltage drops about 20% of the range available in LiPo batteries. Voltage sag becomes an issue during the end of the mission when the battery is near empty. If the thrust-to-weight ratio is close to 1, then the voltage sag can hinder the UAV’s ability to maintain proper hover.

The sizing method presented in this paper is recommended if a higher-fidelity propeller efficiency model is employed. In addition, it’s highly probable that the sizing predictions can be achieved if the shape of the UAV is streamlined to decrease the drag. Future work for the project is to implement algorithms that perform automatic transitions. The flight controller for this UAV can be replaced with programmable off-the- shelf boards to implement optimal transition paths. Other future work is to implement an electric ducted fan into the sizing and develop a working prototype to test the fidelity of EDFs. The advantages of an EDF are its larger thrust and smaller diameter.

REFERENCES

[1] Watts, A., Ambrosia, V., and Hinkley, E., “Unmanned Aircraft Systems in Remote Sensing and Scientific Research: Classification and Considerations of Use,” Remote Sensing, Vol. 4, No. 6, 2012, pp. 1671-1692. [2] Austin, R., Unmanned Aircraft Systems: Uavs Design, Development And Deployment, Wiley, Chichester, UK, 2010. [3] Segarra, L., “This Racing Drone Just Set a Guinness World Speed Record,” Fortune [online], July 2017, http://fortune.com/2017/07/14/fastest-drone-guinness-world- record/. [4] Radhakrishnan, A., “An Experimental Investigation of Ground Effect on a Quad Tilt Rotor in Hover and Low Speed Forward Flight,” Ph.D thesis, Univ. Maryland, College Park, MD, 2006. [5] Gloudemans, J., McDonald, R., Moore, M., Hahn, A., Fredericks, B., and Gary, A., “Open Vehicle Sketch Pad,” OpenVSP [online], 2018, http://openvsp.org/. [6] Tyan, M., Nguyen, N., Kim, S., and Lee, J., “Comprehensive Preliminary Sizing/Resizing Method for a Fixed Wing – VTOL Electric UAV,” Aerospace Science and Technology, Vol. 71, December 2017, pp. 30-41. [7] Bershadsky, D., Haviland, S., and Johnson, E., “Electric Multirotor UAV Propulsion System Sizing for Performance Prediction and Design Optimization,” Proceedings of the 57th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, San Diego, CA, 2016, pp. 1-22. [8] Navarathinam, N., Lee, R., and Chesser, H., “Characterization of Lithium-Polymer Batteries for CubeSat Applications,” Acta Astronautica, Vol. 68, No. 11-12, 2011, pp. 1752-1760. [9] Gatti, M., “Design and Prototyping High Endurance Multi-Rotor,” Ph.D thesis, Univ. Bologna, Bologna, Italy, 2015. [10] Katz, J., and Plotkin, A., Low-Speed Aerodynamics, Cambridge University Press, Cambridge, UK, 2001. [11] Maskew, B., “Program VSAERO Theory Document,” NASA TR-4023, September 1987. [12] Epton, M. and Magnus, A., “PAN AIR - A Computer Program for Predicting Subsonic or Supersonic Linear Potential Flows about Arbitrary Configuration Using a Higher Order Panel Method,” NASA TR-3253, December 1981.

[13] Ashby, D., Dudley, M., Iguchi, S., Browne, L., and Katz, J., Potential Flow Theory and Operation Guide for the Panel Code PMARC 12, NASA, Washington, DC, 1992. [14] Boschitsch, A., Curbishley, T., Quackenbush, T., and Teske, M., “A Fast Panel Method for Potential Flows about Complex Geometries,” Continuum Dynamics, Inc., TR-MSA005, Ewing Township, NJ, January 1996. [15] Willis, D., “An Unsteady, Accelerated, High Order Panel Method with Vortex Particle Wakes,” Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, MA, 2006. [16] Eller, D. and Carlsson, M., “An Efficient Aerodynamic Boundary Element Method for Aeroelastic Simulations and its Experimental Validation,” Aerospace Science and Technology, Vol. 7, No. 7, 2003, pp. 532-539. [17] Kinney, D., “Aero-Thermodynamics for Conceptual Design,” Proceedings of the 42nd AIAA Aerospace Sciences Meeting, Reno, NV, 2004, pp. 1-11. [18] Filkovic, D., “Graduate Work,” Master’s thesis, Univ. Zagreb, Zagreb, Croatia, 2008. [19] XFLR5, “Homepage,” XFLR5 [online], 2017, http://www.xflr5.com/xflr5.htm. [20] Drela, M., and Youngren, H., “Athena Vortex Lattice (AVL),” MIT [online], 2016, http://web.mit.edu/drela/Public/web/avl/. [21] Raymer, D., Aircraft Design: A Conceptual Approach, Institute of Aeronautics and Astronautics, Washington, DC, 1992. [22] Gudmundsson, S., General Aviation Aircraft Design: Applied Methods and Procedures, Elsevier Science & Technology, St. Louis, MO, 2014. [23] Gundlach, J., Designing Unmanned Aircraft Systems, American Institute of Aeronautics & Astronautics, Reston, VA, 2014. [24] Roskam, J., Airplane Design, Part V: Component Weight Estimation, DARcorporation, Lawrence, KS, 1985. [25] Roskam, J., Airplane Design, Part I: Preliminary Sizing of Airplanes, DARcorporation, Lawrence, KS, 1985. [26] MIT, “Lab 8 Notes – Basic Aircraft Design Rules,” MIT [online], 2006, https://ocw.mit.edu/courses/aeronautics-and-astronautics/16-01-unified-engineering-i- ii-iii-iv-fall-2005-spring-2006/systems-labs-06/spl8.pdf. [27] Roskam, J., Airplane Design, Part II: Preliminary Configuration Design and Integration of the Propulsion System, DARcorporation, Lawrence, KS, 1985. [28] Hrishikeshavan, V., and Chopra, I., “Design and Testing of a Dual Tilt-Wing Micro Air Vehicle,” Proceedings from the 68th Annual Forum American Helicopter Society, Fort Worth, TX, 2012, pp. 1-17. [29] Ryan Aeronautical Company, Propeller Static Thrust, Ryan Aeronautical Company, San Diego, CA, 1955.

[30] Hepperle, M., “JavaProp - Design and Analysis of Propellers,” JavaProp [online], 2016, https://www.mh-aerotools.de/airfoils/javaprop.htm.

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APPENDIX

FW FLIGHT RAW DATA PLOTS

Figure A.1. FW flight - Pilot signal inputs.

Figure A.2. FW flight - Power draw.

101

Figure A.3. FW flight - Ground altitude from GPS.

Figure A.4. FW flight - Ground speed data from GPS.

Figure A.5. FW flight - Total altitude data from GPS.

102

Figure A.6. FW flight - Total current draw.

Figure A.7. FW flight - Battery supply voltage.

Figure A.8. FW flight - Left motor RPM.