Design and Implementation of a Belted Alternator Starter System for the OSU Ecocar 3 Vehicle THESIS

Home , Alternator (automotive), Belt (mechanical), Electric machine, Electric motor, Mild hybrid, Motor drive

Design and Implementation of a Belted Alternator Starter System for the

OSU EcoCAR 3 Vehicle

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

Dennis Ssebina Kibalama

Graduate Program in Electrical and Computer Science

The Ohio State University

2017

Master's Examination Committee:

Dr. Giorgio Rizzoni, Advisor

Dr. Levent Guvenc

Dr. Shawn Midlam-Mohler

Copyrighted by

Dennis Ssebina Kibalama

2017

Abstract

The transportation sector is a great contributor to overall energy consumption and emissions. Stringent regulations have been put in place to curb the emissions and regulate fuel consumption due to dependency on a finite resource, fossil fuels. This has driven

OEMs to re-engineer the automotive powertrain which has led to a burst in production of

PHEVs, HEVs and EVs. The U.S. D.O.E, General Motors, Argonne National Laboratory

(ANL) and other industry sponsors have spearheaded (Advanced Vehicle Technology

Competitions) AVTCs with a goal of training the next generation of automotive engineers by challenging collegiate teams to re-engineer stock vehicles to improve fuel consumption, reduce emissions while maintaining consumer acceptability. The latest in this AVTC series is the EcoCAR 3, a 4-year competition which challenges 16 North American university teams to re-engineer a 2016 Chevrolet Camaro into a HEV while maintaining the performance aspects of the iconic American car.

The OSU EcoCAR 3 vehicle boasts a Parallel-series post transmission PHEV architecture designed by the team in Year 1 of the competition. To meet the team designed (Vehicle

Technical Specification) VTS targets, the architecture includes a motor coupled to the engine, a Belted Alternator Starter (BAS) which performs engine start/stop, series operation, speed matching and torque assist. Due to the versatility of the component in

ii realizing the VTS targets, this thesis sets to outline the design and validation work done with regards to the BAS system.

The BAS system consists of the electric machine, the engine, belt transmission, inverter and battery pack. The thesis outlines the design metrics considered in the design of the

BAS system ranging from electrical, performance, mechanical and thermal considerations.

The BAS chosen is a sponsor donated component that wasn't supplied with an inverter solution. This thesis details the two inverter choices adopted over Years 2 – 3 of the competition and the control, calibration, validation, performance and packaging carried out to realize functionality of the BAS. To accurately model the dynamics of the BAS system during engine startup, a dynamic engine model is developed to model engine, BAS and belt transmission dynamics. The underlying assumptions made to develop an accurate representation of the dynamics while minimizing calibration efforts are also outlined. This model will be used in Year 4 for development and optimization of an engine start/stop controller. The thesis also analyses the two control methods adopted for engine start; an open loop controller and a closed loop controller and evaluates the performance of the controllers in terms of rise time, engine speed overshoot, maximum jerk and root mean square acceleration. This thesis encompasses the design and validation work done to move the BAS system development work from a component/subsystem level to vehicle/system level. This sets the team in a good position heading into Year 4 of the competition to implement engine start/stop functionality in the vehicle, optimize torque assist functionality and use the BAS for speed matching for faster shift times.

iii

Acknowledgments

I am indebted to the entire support of the people at the OSU Center for Automotive

Research. I would like to thank Dr. Giorgio Rizzoni and Dr. Shawn Midlam-Mohler for not only the opportunity to work with the OSU EcoCAR team but also their guidance and tutelage as I pursued graduate studies; their ideas, thought processes and drive were instrumental in my time at The Ohio State University. I'd like to acknowledge my fellow

EcoCAR team members who were very resourceful and hardworking individuals dedicated to applying their engineering skills and knowledge to solve engineering challenges and achieve a well-engineered Camaro. Shout out to Aditya Modak, Andrew Huster, Andrew

Johnson, Arjun Khanna, Brandon Bishop, Greg Jankord, Kristina Kuwabara, Nick

Tomczack, Simon Trask and Wilson Perez. A special shout out to Andrew Huster and his family for making my experience in a new country memorable. You surely made Ohio a home away from home. I am indebted to Kiira Motors Corporation for facilitating my pursuit for higher education; none of this would have been possible without them. I am thankful for my family and friends in Uganda that have supported me throughout my pursuit of graduate studies. Finally, I'm thankful to the EcoCAR organizers and sponsors that make this an invaluable learning experience for everyone involved with AVTCs.

Vita

October 24, 1990 ...... Born – Kampala, Uganda

2008...... Makerere College School, Uganda

June 2013 ...... B.S. Electrical Engineering, Makerere

University, Uganda

August 2014 to present ...... Graduate Research Associate, Department of

Electrical and Computer Engineering, The

Ohio State University.

Publications

D. Kibalama, A. Huster, A. Khanna, A. Modak, M. Yasko, G. Jankord and S. Midlam-

Mohler. “Testing and Validation of a Belted Alternator Starter System for a Post-

Transmission Parallel PHEV for the EcoCAR 3 Competition”. SAE Technical Paper,

2017-01-1263, Oct. 2016.

Fields of Study

Major Field: Electrical and Computer Engineering

Table of Contents

Abstract ...... ii

Acknowledgments ...... iv

Vita ...... v

Publications ...... v

Fields of Study ...... v

Table of Contents ...... vi

List of Tables ...... xi

List of Figures ...... xii

List of Acronyms ...... xv

Chapter 1: Introduction ...... 1

1.1. Energy Trends Analysis and Motivation ...... 1

1.2. AVTCs & The EcoCAR 3 Competition ...... 3

1.3. Vehicle Architecture ...... 5

1.4. Vehicle Technical Specifications ...... 6

1.5. Objectives ...... 7

1.6. Thesis Overview ...... 7 vi Chapter 2: Literature Review ...... 9

2.1. Introduction ...... 9

2.2. Drivetrain Electrification ...... 9

2.2.1. Hybrid Electric Vehicles (HEVs) ...... 10

2.2.2. Plugin Hybrid Electric Vehicles (PHEVs) ...... 11

2.2.3. HEV & PHEV Configurations ...... 12

2.2.4. Degrees of Hybridization ...... 15

2.3. Inverter Control ...... 16

2.4. Drive Quality and NVH ...... 17

2.4.1. Engine start/stop times ...... 18

2.4.2. Jerk ...... 18

2.4.3. Root Mean Square Acceleration ...... 18

2.4.4. Vibration Dose Value (VDV) ...... 19

Chapter 3: System Design Considerations ...... 20

3.1. Introduction ...... 20

3.2. Electrical System Evaluation ...... 20

3.2.1. Voltage Range ...... 20

3.2.2. Electrical Power and Current ...... 21

3.2.3. Wire and Fuse Sizing ...... 22

vii 3.2.4. Back EMF considerations ...... 24

3.3. Machine Performance Characteristics ...... 25

3.4. Mechanical Integration ...... 26

3.4.1. ISG vs. BAS ...... 26

3.4.2. Belt Coupling ...... 27

3.5. Thermal Considerations ...... 29

Chapter 4: Inverter Evaluation and Validation ...... 31

4.1. Infineon HybridKit 2 ...... 31

4.1.1. LV System Validation ...... 33

4.1.2. HV System Validation ...... 35

4.1.3. Inverter Enclosure Design ...... 37

4.1.4. Inverter Control ...... 37

4.2. Rinehart PM100DX ...... 42

4.2.1. Inverter Calibration ...... 44

4.2.2. Performance Validation ...... 44

4.2.3. Thermal Validation ...... 45

4.3. BAS System Technical Specification ...... 49

Chapter 5: System Modeling ...... 50

5.1. BAS model ...... 51

viii 5.2. Engine model ...... 52

5.2.1. Crankshaft Kinematics ...... 52

5.2.2. Indicated Torque ...... 54

5.2.3. Inertial Torque ...... 57

5.2.4. Friction Torque ...... 57

5.2.5. Thermal Model ...... 58

5.3. Belt Transmission Model ...... 60

5.3.1. Assumptions ...... 61

5.4. Model Calibration and Validation ...... 63

5.4.1. Friction Parameter Calibration ...... 63

Chapter 6: Engine Start Control ...... 65

6.1. Control Problem Definition ...... 65

6.1.1. Engine Starts ...... 66

6.1.2. Engine Stops ...... 66

6.2. Exponential Speed Profiles ...... 68

6.3. Objective Function ...... 70

6.4. Open Loop Engine Start Controller ...... 74

6.5. Closed Loop Engine Start Controller ...... 77

6.5.1. Tuned Closed Loop Controller ...... 80

ix 6.5.2. Various Engine Starts ...... 82

6.6. Summary ...... 83

Chapter 7: Conclusions and Future Work ...... 84

7.1. Work Done ...... 84

7.2. Future Work ...... 85

References ...... 87

List of Tables

Table 1: Vehicle Technical Specifications ...... 6

Table 2: HV Component Voltage Ratings ...... 21

Table 3: HV component Power and Current ...... 21

Table 4: BAS System Coupling ...... 28

Table 5: Infineon Hybrid Kit Specifications ...... 31

Table 6: Instrumentation used for HV testing ...... 36

Table 7: PM100DX Specification ...... 43

Table 8: BAS System Specification ...... 49

Table 9: BAS System Calibration Parameter ...... 63

Table 10: Minimum values for optimization function ...... 71

Table 11: Optimal reference engine start profile parameters ...... 72

Table 12: Open Loop controller parameters ...... 76

Table 13: Closed loop controller parameters ...... 79

Table 14: Tuned closed loop controller parameters ...... 81

Table 15: Various engine starts - parameter evaluation ...... 83

List of Figures

Figure 1: US Energy Consumption in the Transport Sector (1960-2015) [2] ...... 1

Figure 2: Average MPG in the US (1960-2015) [3] [4] ...... 2

Figure 3: EcoCAR 3 Vehicle Development Process (VDP) ...... 4

Figure 4: Systems Engineering V diagram [5] ...... 4

Figure 5: OSU EcoCAR 3 Vehicle Architecture ...... 5

Figure 6: Conceptual visualization of a Series configuration [9] ...... 13

Figure 7: Conceptual visualization of Parallel configuration [9] ...... 14

Figure 8: FOC for an AC machine [13] ...... 17

Figure 9: 35mm2 wire specification [15] ...... 23

Figure 10: HV Component Layout showing BAS system wire sizes ...... 24

Figure 11: Normalized Back EMF vs. speed ...... 25

Figure 12: Motoring region of operation [16] ...... 26

Figure 13: Engine drive pulley ...... 28

Figure 14: BAS – Engine coupling ...... 29

Figure 15: Electronics Cooling Loop ...... 30

Figure 16: Infineon HybridKit 2 ...... 32

Figure 17 Inverter LV calibration setup ...... 34

Figure 18: Inverter packaging detailing HV connections ...... 35

xii Figure 19: HV Test Setup ...... 36

Figure 20: Packaged inverter fully integrated in-vehicle ...... 37

Figure 21: Control implemented for BAS inverter ...... 38

Figure 22: Controller performance at a steady state condition of 5Nm at 1300 rpm ...... 39

Figure 23: Controller performance during transient operation (5Nm, 1300 rpm to 10Nm,

1300 rpm) ...... 40

Figure 24: Higher Torque region of operation ...... 41

Figure 25: Analysis of inverter performance ...... 42

Figure 26: Rinehart PM100DX ...... 43

Figure 27: Experimental data torque-speed curve ...... 45

Figure 28: Steady state BAS testing at 30Nm, 3600 rpm ...... 46

Figure 29: BAS Peak region testing from 30Nm at 3000 rpm to 46Nm at 5500 rpm ...... 48

Figure 30: BAS system model overview ...... 50

Figure 31: BAS torque-speed curve ...... 51

Figure 32: Crank slider mechanism [18] ...... 53

Figure 33: Belt Transmission ...... 60

Figure 34: Comparison of BAS and Engine Speeds ...... 62

Figure 35: Engine start showing engine speed overshoot ...... 66

Figure 36: Engine stop showing engine speed undershoot ...... 67

Figure 37: Exponential engine start profiles ...... 69

Figure 38: Exponential engine stop profiles ...... 70

Figure 39: Variation of metrics for various time constants ...... 72

Figure 40: Cost vs. � [��] ...... 73

xiii Figure 41: Optimal reference engine start profile ...... 74

Figure 42: Open loop controller response ...... 75

Figure 43: Closed loop controller structure ...... 77

Figure 44: Closed loop controller response ...... 78

Figure 45: Closed Loop controller tuned response ...... 80

Figure 46: Engine starts for various engine temperatures ...... 82

xiv

List of Acronyms

AC – Alternating Current

AVTC – Advanced Vehicle Technology Competition

BAS – Belted Alternator Starter

CAN – Controller Area Network

DC – Direct Current

ECM – Engine Control Module

ESS – Energy Storage System

EV – Electric Vehicle

HEV – Hybrid Electric Vehicle

HSC – Hybrid Supervisory Controller

HV – High Voltage

ICE – Internal Combustion Engine

NVH – Noise, Vibration and Harshness

PHEV – Plug-in Hybrid Electric Vehicle

VTS – Vehicle Technical Specifications

Chapter 1: Introduction

1.1. Energy Trends Analysis and Motivation

The transportation sector is the second largest contributor to Green House Gas (GHG) emissions totaling about 27% of the total US emissions in 2013. The transportation sector accounted for 27.5% of the US energy use by sector in 2014 [1].

Figure 1: US Energy Consumption in the Transport Sector (1960-2015) [2]

As shown in Figure 1, the energy used by the transportation sector has increased over the years and is projected to continue along a similar trend. The stringent regulations imposed on fuel economy and emissions have prompted automotive OEMs to re-engineer the powertrain to meet these regulations; which correlates to increasing MPG over the years as shown in Figure

Figure 2: Average MPG in the US (1960-2015) [3] [4]

The ever-increasing consumer demands, and stringent regulations on emissions and fuel consumption drove the automotive OEMs to re-engineer the drivetrain of the vehicle. This has ranged from engine downsizing, and innovative solutions that improve the efficiency of

ICEs to various levels of drivetrain electrification/hybridization. The need for alternative 2

energy vehicles has been driven by the necessity to make a shift from petroleum to cap dependency on a finite resource and shift to alternative sources of energy for propulsion power. As an intervention, the U.S. DOE has over the years organized various series of

AVTCs in collaboration with industry sponsors and ANL to train the next generation of automotive engineers. They are tasked with applying innovative solutions to re-engineer the vehicle powertrain with an end goal of meeting the ever-changing consumer demands and stringent regulations governing the automotive industry. The latest in this series of AVTCs is the EcoCAR 3 competition.

1.2. AVTCs & The EcoCAR 3 Competition

EcoCAR 3 competition is the latest in the series of AVTCs that challenges 16 North American universities to re-engineer a 2016 Chevrolet Camaro into a performance hybrid electric vehicle. The competition is managed by ANL and the headline sponsors are General Motors and the U.S. DOE. The competition goals are:

• Increasing the fuel economy of the vehicle

• Minimizing GHG and criteria emissions

• Petroleum use reduction

• Maintaining and/or improving performance and consumer acceptability

The EcoCAR 3 competition is a 4-year competition that implements the Vehicle Development

Process (VDP) shown in Figure 3.

Figure 3: EcoCAR 3 Vehicle Development Process (VDP)

To achieve the goals set forth by the competition, the OSU EcoCAR team employed a development process that followed both the EcoCAR VDP and a V diagram based systems engineering approach in Figure 4. The goal of this was to mirror standard VDP practices employed in the automotive industry.

Figure 4: Systems Engineering V diagram [5]

1.3. Vehicle Architecture

With the end goal of meeting the team defined Vehicle Technical Specifications (VTS) targets, the OSU EcoCAR team is developing a Parallel-Series Plug-in Hybrid Electric

Vehicle (PHEV) with the architecture shown in Figure 5.

Figure 5: OSU EcoCAR 3 Vehicle Architecture

The OSU team vehicle architecture consists of a 119kW 2.0L GDI in-line 4 engine which is belt coupled via the engine accessory drive pulley to a 32kW electrical machine; colloquially referred to as the Belted Alternator Starter (BAS). The engine flywheel is then coupled to a 5- speed automated manual transmission via a clutch. The clutch is controlled by a CAN controlled hydraulic clutch actuator. The AMT is a manual transmission that is automated by the team to have better control over shift points and efficiency. The transmission output shaft connects to a team designed Power Transfer Unit (PTU) which is also connected to a 112kW

Rear Electric Machine (REM). The output of the PTU is connected to the rear wheels via a differential. The powertrain maintains the RWD aspect of the stock vehicle. The HV electrical system is powered by an 18.9 kWh Li-ion phosphate Energy Storage System (ESS) which supplies power to the BAS, REM, DC/DC converter and HV (Heating Ventilation and Air

Conditioning) HVAC compressor module. The team also incorporated an onboard charger, a

3.3kW BRUSA NLG513 charger that offers plug in charging capability.

1.4. Vehicle Technical Specifications

The vehicle architecture adopted by the team can meet and/or even exceed the performance

VTS are targets and requirements that represent the energy consumption, performance, utility and emissions metrics of the team designed vehicle. Emissions and energy consumption targets in initial modeling were consistent with the needs of the target customers. Table 1 compares the competition VTS targets with the team developed VTS.

Table 1: Vehicle Technical Specifications

Specification Units Targets Team VTS Acceleration, IVM-60 mph sec 5.9 7.5 Acceleration, 50-70 mph (passing) sec 7.3 8 Braking, 60-0 mph ft. 128 120 Acceleration Events Torque Split (Front/Rear) % RWD RWD Lateral Acceleration, 300 ft. Skid Pad G 0.85 0.9 Highway Gradeability, @ 20 min, 60 mph % 6 6 Total Vehicle Range* mi N/A 272.9 CD Mode Range* mi N/A 43.78 CD Mode Total Energy Consumption* Wh/km N/A 219.9 CS Mode Fuel Consumption* Wh/km N/A 558.1 UF-Weighted Total Energy Consumption* mpgge 30 30.06 UF-Weighted WTW Petroleum Energy Use* Wh PE/km 420 58.7

The BAS system which is the subject of this thesis plays an instrumental role in achieving the numerous VTS targets for example 0 – 60 mph acceleration, total vehicle range, CS mode total energy consumption, etc.

1.5. Objectives

The objectives of this thesis are:

• To detail the methodology adopted and metrics evaluated in the design of the BAS

system while highlighting the rationale for the design decisions made

• Evaluate the two inverter choices adopted by the team over Years 2 and 3 of the

competition and detail the design and validation work done on each of the inverters

• Develop a model of the BAS system to account for dynamics that occur during engine

starts/stops. This model shall be calibrated and utilized in Year 4 for developing an

engine start/stop controller.

• Evaluate the performance of the BAS system with open loop and closed loop engine

start control strategies and quantify metrics of performance and NVH

• Lay the groundwork for optimization of engine start/stop that will be implemented on

the vehicle in Year 4 of the competition.

1.6. Thesis Overview

This thesis discusses the design metrics evaluated to design a BAS system for the OSU

EcoCAR 3 vehicle with a goal of meeting the VTS targets set forth by the team. It then details the two inverter choices adopted by the team. This is followed by developing a model for the

BAS system that will be used in Year 4 for engine start/stop validation and an evaluation of the current engine start controller implemented in the vehicle. The outline is as shown below:

• Chapter 2 reviews hybridization trends in the automotive industry with keen attention

to alternator starter systems and start/ stop systems. It also evaluates different methods

used to quantitatively evaluate drivability and NVH, vehicle criteria that are even more

important to realize synergy with hybrid powertrains

• Chapter 3 discusses the design metrics considered and evaluated in the design of the

BAS system for the EcoCAR vehicle. These include performance, electrical,

mechanical and thermal aspects of the BAS system.

• Chapter 4 details the inverter choices adopted by the team over Years 2 and 3 of the

competition. This involves inverter selection, controls development and validation,

packaging and the pros and cons of the two inverter choices.

• Chapter 5 describes the modeling activities to develop a higher fidelity BAS system

model capable of approximating dominant engine dynamics occurring during engine

starts and stops. This will be instrumental in engine start/stop controller

implementation on the vehicle in Year 4 of the competition.

• Chapter 6 describes the control problem definition regarding engine starts/stops and

describes the development work done to achieve engine start functionality in Year 3.

The performance of this controller is evaluated.

• Chapter 7 summarizes the work done throughout the thesis and draws important

conclusions and setbacks faced while pursuing this thesis. It also lays the groundwork

for future work regarding the BAS system

Chapter 2: Literature Review

2.1. Introduction

This chapter provides an overview to drivetrain electrification and the various Hybrid Electric

Vehicle architectures. Further detail is paid to starter/alternator systems in various levels of hybridization. Relevant literature regarding inverter control techniques and an overview of the metrics to be evaluated with regards to drive quality, engine start times and NVH is also covered

2.2. Drivetrain Electrification

Owing to significant strides in battery research, electric machine design, power electronics and the stringent regulations on emissions and fuel consumption, automotive OEMs have explored production of electric vehicles (EVs) which has led to increased production and registration of electric and hybrid cars [6]. EVs have an onboard battery pack, one or more electric machines and no ICE which implies that they are characterized by zero tailpipe emissions and high efficiency due to the high efficiencies of battery packs and electric machines relative to ICEs. Despite the increase in EVs over the years and associated advantages, there are still some factors hindering their wide adoption; high cost of batteries and electric machines hence high initial vehicle cost, low energy density of batteries relative to fuel used in ICEs, low total vehicle range, battery degradation, under developed charging network grid and long charging times. Some automotive OEMs are looking to break this

barrier e.g. Tesla through extensive research and lowering costs of production but on a general scale, wide adoption of EVs is still a few years away. A compromise that leverages the advantages of both EVs and conventional vehicles is a more viable option that is being adopted by automotive OEMS, hence drivetrain electrification.

Drivetrain electrification refers to adding electronic propulsion components (batteries, electric machines, power electronics, ultra-capacitors, etc.) to the powertrain and/or driveline in a bid to leverage the advantages of electrified powertrain while maintaining core aspects of a conventional drivetrain. Per many automotive manufacturers, it will be impossible to achieve emission and fuel consumption targets without drivetrain electrification [7]. Drivetrain electrification ranges from start-stop technology, electric machines/modules used in various configurations as will be discussed later in this chapter, electric axles, in wheel motors, electric wheel drive systems, etc. [7].

Hybrid propulsion has emerged as the most viable option of drivetrain electrification and involves combining electric drive units with ICEs in a bid to improve fuel consumption and lower GHG and criteria emissions. Hybrid vehicles are already in production and have shown savings of up to 25% in fuel [8].

2.2.1. Hybrid Electric Vehicles (HEVs)

A HEV typically has 2 types of energy sources that are used to propel the vehicle; electricity and fuel. The fuel can be any type of fossil fuel (gasoline, diesel, ethanol, E85, E10, B10, etc.) stored in a fuel tank. The electricity is stored in a battery or sometimes both a battery and

ultra-capacitors. The most common energy form used for storing electrical energy is a battery pack and will be referred to as an Energy Storage System (ESS) from hereon.

In HEVs, an ICE works together with one or more electric motors to provide propulsion force.

Since there is at least one more source of propulsion force other than the engine, the engines in HEVs are typically downsized in a bid to improve overall vehicle fuel consumption while still having the capability of meeting the driver’s torque request. HEVs are operated in charge sustaining mode with the goal of ensuring that the battery remains charged and thus don’t require to be plugged in to charge the battery. The electric motors have the capability of recuperating some of the kinetic energy of the vehicle that would otherwise be lost through heat and convert this into electrical energy that is stored in the ESS; a phenomenon known as regenerative braking. The high efficiency of the electrical system, regenerative braking capability, engine downsizing and extra degree(s) of freedom of torque production make

HEVs more appealing to automotive OEMs. On the downside, HEVs are more expensive than conventional vehicles due to use of a HV ESS and one or more electric motors [9] [10]. Some examples of HEVs currently on the market are the 2017 Buick Lacrosse HEV, Toyota Prius, and Ford Fusion Hybrid.

2.2.2. Plugin Hybrid Electric Vehicles (PHEVs)

A PHEV is a HEV with a larger capacity battery pack that can be plugged into the electrical grid for charging. The larger capacity battery pack implies that PHEVs have all-electric range, a feature that HEVs lack. PHEVs can be operated in both Charge Depleting (CD) and Charge

Sustaining (CS) modes. PHEVs can be operated first as EVs until the electric range is

exhausted and then the ICE can be used to propel the vehicle while sustaining the state of charge of the ESS. Another implementation can be to operate the vehicle as an HEV with a higher cost penalty imposed on using the ICE in a bid to use the more efficient electric powertrain to meet the driver’s torque request as opposed to using the engine. PHEVs combine the all-electric range of EVs and the better fuel economy and lower emissions of HEVs. Due to having a larger capacity ESS, PHEVs are more expensive than HEVs and are hugely affected by issues of long charging times which poses a problem to their wide adoption by the public. Some examples of PHEVs currently on the market are the Chevrolet Volt, Audi A3 e-

Tron, Ford C-Max Energi and the Toyota Prius Prime.

2.2.3. HEV & PHEV Configurations

HEVs and PHEVs can be broadly categorized into three major configurations i.e. Series,

Parallel and Parallel – Series configurations which are explained in the following section.

Series Configuration

In a series architecture, the ICE is coupled to a generator and the ICE isn’t directly coupled to the wheels. Traction force is provided by one or more electric motors that are coupled to the wheels. A conceptual visualization of a series architecture is shown in Figure 6. The advantages of this architecture are its ease of implementation from a packaging and controls perspective. The high efficiency of the electric motors across its entire torque-speed region dictate that a single speed or 2 speed gearbox can be implemented. Since the engine is completely decoupled form the wheels, the ICE can be operated in its most efficient region ensuring low fuel consumption. The disadvantage of a series powertrain architecture are the

high costs associated since the vehicle should have at least 2 electric motors with the traction motor largely sized to meet all the driver torque requests. Series powertrains are usually implemented in large vehicles that have enough space for the engine/generator set [10].

Figure 6: Conceptual visualization of a Series configuration [9]

Parallel Configuration

In a parallel configuration, the engine and electric motor can both supply torque to the wheels.

A conceptual visualization of a parallel configuration is shown in Figure 7 with the electric motor located post transmission. Another parallel configuration exists where the electric motor can be located pre-transmission. With this configuration, the complexity of packaging and control increases but if implemented correctly, the advantages of this configuration can

outweigh the cons of having a series configuration. It is characterized by less energy losses since chemical energy from the engine is converted directly to mechanical energy. Due to compactness of this configuration, this has been adopted in passenger cars like the Honda

Insight and Ford Escape [10].

Figure 7: Conceptual visualization of Parallel configuration [9]

Parallel-Series Configuration

This leverages the advantages of both the series and parallel configurations. It is also known as a multi-mode or power-spit configuration because it can perform as a series configuration when the engine is decoupled from the wheels through a planetary gearset or other mechanical coupling and ability to perform as a parallel configuration when the engine is mechanically coupled to the wheels. This configuration adds extra complexity in implementation and

control and extra cost compared to a parallel configuration. However, the benefits of this architecture have seen it prevail as the most prominent HEV architecture implemented in most production hybrids. The Toyota Prius employs this configuration [10]. The OSU EcoCAR vehicle architecture is also a parallel-series configuration.

2.2.4. Degrees of Hybridization

PHEVs and HEVs can also be categorized according to the balance between electric and ICE power provided to the wheels i.e. Micro, Mild, or Full Hybrids.

Micro Hybrids

These typically utilizes start-stop technology and includes a 36V - 48V battery to power on board electrical systems. The motors in micro hybrids are typically not used to drive the wheels but instead reduce the burden on the ICE. Examples include the Chevrolet Malibu with stop-start and Mazda’s i-ELOOP system. [11]

Mild Hybrids

Mild hybrids comprise of small sized HV battery packs capable of powering a motor that supplies torque to the wheels. The motor alone is usually not capable of providing all the propulsion torque and hence the vehicle is operated in a charge sustaining strategy. Engine start-stop technology can be implemented. Since the engine is on most of the time, mild hybrids don’t return significantly greater improvements to EPA rated fuel consumption. The higher voltage batteries ensure less current, smaller size wire and less losses hence higher power motors can be used. Mild hybrids leverage the advantages of the higher voltage levels

while eliminating high costs associated with larger batteries and motors. Examples of vehicles with Mild hybrid systems are Honda CR-Z equipped with Honda Integrated Motor Assist

(IMA) and the Chevrolet Malibu with eAssist.

Full Hybrid Systems

These have large battery packs and motors capable of providing traction force. These tend to have an all-electric range and then transition to a charge sustaining strategy to maintain the charge on the battery between given set-points while relying largely on the ICE to meet the driver’s torque request in CS mode. Examples of these include the Chevrolet Volt and the

Prius.

2.3. Inverter Control

The basis of AC motor control is Field Oriented Control (FOC) where the stator currents of an AC machine are converted into a time invariant orthogonal axis. This is based on reference frame theory which transforms a 3-phase time and speed based system (a, b, c reference frame) into a 2-coordinate time invariant system (d, q reference frame) [12]. This transformation transforms the complex AC machine control into a simpler form similar to that of DC machine control. This is achieved through Park and Clarke transformations [12]. The two input control parameters then become the torque component (which is aligned with the q axis coordinate) and the flux component (which is aligned with the d component). Figure 8 shows the general structure of a FOC controller which requires two reference inputs � and �.

Figure 8: FOC for an AC machine [13]

2.4. Drive Quality and NVH

According to [14], drive quality is a comprehensive term that encompasses vehicle responsiveness, and driving comfort. With regards to engine start/stop, drive quality can be quantified in terms of how fast the engine starts up and the frequency of engine starts and stops. The operating smoothness with regards to engine start/stop relates to NVH that may be experienced by a driver during a start and stop event.

2.4.1. Engine Start/Stop Times

Despite the advantages presented by engine start/stop of reducing engine idle time. There are drawbacks to engine start/stop if not controlled appropriately. Frequent engine starts/stops can lead to more fuel consumption and worse emissions especially during cold start operation.

Frequent engine starts can also pose a driveability concern and the number of engine starts/stops needs to be controlled. It is desirable to keep engine start/stops to a minimum to maintain a compromise between fuel consumption improvements and driveability concerns.

2.4.2. Jerk

Jerk is the derivative of acceleration and represents changes in acceleration or deceleration in

�/� [14]. The most important quantity of measurement is the maximum Jerk as this is the maximum rate of change of acceleration that the driver is likely to experinece.

2.4.3. Root Mean Square Acceleration

This is an objective measure of the average acceleration that occurs during a defined time period. When carried out and normalized over an 8 hour period of time, it is referred to as the

A(8) method [14]. The root mean square acceleration is expressed by equation (1)

� � = �� 1 (� − � )

The acceleration is filtered using a bandpass filter for the bandwidth ranging from 1 to 32 Hz since this is the frequency range for perception of vibration by humans [14]

2.4.4. Vibration Dose Value (VDV)

Vibration Dose Value is a qualitative way of determining the vibration felt by being in contact with a vibrating surface over a defined period time. The VDV is defined by equation (2)

�� = � � �� 2

Similarly, the acceleration is filtered in the range of 1-32 Hz.

Chapter 3: System Design Considerations

3.1. Introduction

This chapter details the various metrics considered while designing and integrating the BAS system. These range from electrical, performance, mechanical and thermal considerations.

3.2. Electrical System Evaluation

This section details the various metrics evaluated regarding the electrical system. This involves the voltage ranges of the components, the wire and fuse sizing for the HV system with keen attention to the BAS system, continuous and peak power and current draws of the components, and back EMF considerations.

3.2.1. Voltage Range

The initial choice was the voltage level adopted for the starter/alternator. A preliminary analysis of the pros and cons of the 12V, 36V - 48V and full hybrid starter/alternator systems revealed that the full hybrid system had the highest power output with a drawback of high cost. Since the team was developing a PHEV with an 18.9kWh battery pack available to the team, a HV starter/alternator was chosen over the other configurations.

The next step was ensuring that the voltage ranges of the selected components matched without having under-voltage and/or over-voltage fault out conditions occurring on any of the components. Table 2 shows the BAS system HV component voltage ratings.

Table 2: HV Component Voltage Ratings

HV Component Min. Voltage Max. Voltage Nominal Voltage ESS 263 378 340 BAS 0 400 -

As seen in Table 2, the BAS voltages are well within the minimum and maximum voltages of the ESS. The bottleneck in the system is the ESS which with HV contactors closed supplies a voltage ranging from 263 – 378 VDC. This ensures that no under-voltage or over-voltage faults will be tripped on the system.

3.2.2. Electrical Power and Current

The HV system was designed to ensure that the ESS can support continuous and peak operation of the BAS and the HV components. Table 3 outlines the continuous and peak power and currents for all the HV components integrated in the vehicle.

Table 3: HV component Power and Current

HV Nominal Peak Power Cont. Current Peak Current Component Power kW] [kW] ESS -21 Chg. / 60 -110 Chg. / 177 180 Adc 612 Adc Dis. Dis. BAS 15 32 75 Arms 150 Arms REM 80 112 260 Arms 550 Arms REM inverter 100 150 450 Arms 550 Arms DC/DC 2.2 3.78 1 A 10A HVAC 4.5 12.6 15A 30A Charger 3.3 3.3 7A 9A

The major HV loads on the system are the BAS and the REM system. At peak conditions, assumed to be a 0 – 60 acceleration where the peak power is requested from both components, the BAS has a current draw of 120 Adc and the REM has a current draw of 350 Adc from simulation data. This is still lower than the maximum current that the ESS can provide thus this component sizing ensures that the ESS can support peak component functionality of the

BAS. The peak power of the HV components is 160 kW which is still lower than the peak power that the ESS can support.

It is worth mentioning that the ESS has discharge and charge buffers that determine how much current can be drawn from the ESS without tripping a fault and opening HV contactors. These buffers are monitored by the HSC and the component performance can be derated to ensure that the discharge and charge current limits set by the ESS are respected.

3.2.3. Wire and Fuse Sizing

The wire size was selected based on continuous and peak currents expected from the BAS based on simulation data. 35 mm2 wire was the chosen wire gauge as it can handle the peak currents on the BAS under a myriad of temperature conditions as shown in Figure 9. The selected 35 mm2 wire is rated to handle 250Adc at 140°�. The wire is also rated to handle the voltage since it is rated up to a maximum of 600/900 V AC/DC which is well within the voltage limits expected on the BAS.

Figure 9: 35mm2 wire specification [15]

The BAS system is fused together with all components in the front HV junction box to ensure that both the BAS inverter and the wires from the rear HV junction box to the front junction box are fused. Figure 10 shows the layout of the HV components and a fuse size of 150A was selected for the BAS system to cater for peak loading conditions while avoiding nuisance fuse blows.

Figure 10: HV Component Layout showing BAS system wire sizes

3.2.4. Back EMF Considerations

The chosen electric machine is an interior permanent magnet (IPM) machine which is subject to back EMF since the permanent magnets induce a voltage in the windings as the magnets rotate. The maximum back EMF was determined to be 364 � � from simulation data thus the chosen inverter should have IGBTs capable of handling this voltage in the event of a fault condition. Figure 11 shows the normalized back EMF of the BAS as a function of temperature and BAS speed. To ensure safety, the BAS inverter is not enabled unless the HV contactors have been closed thereby ensuring that the voltage on the HV DC bus is dependent on ESS voltage as opposed to the voltage that might be induced on the HV bus from spinning the BAS. Since the BAS is always coupled to the engine, the HV contactors are always closed when the engine is running to provide a voltage to counter the back EMF that would otherwise be present at the DC terminals of the inverter.

Figure 11: Normalized Back EMF vs. speed

3.3. Machine Performance Characteristics

The torque-speed characteristics of the chosen electric machine are critical based on the application in which it is deployed. For engine start functionality, an electric machine with a high peak torque at low speeds is desirable to provide high torque for starting the engine. This is particularly paramount in cold cranking events and in an effort of achieving fast engine startup times. Figure 12 shows the regions of interest where region A is primarily for engine start and motoring while region B is used for launch assist and speed matching [16].

Figure 12: Motoring region of operation [16]

The chosen BAS has a maximum torque of 60Nm and a rated speed of 4000 rpm. This ensures that the BAS can crank the engine and provide torque to shift loading points for the engine.

To further multiply the torque and match BAS and engine speeds, a gear multiplication was adopted which is discussed in the following section.

3.4. Mechanical Integration

This highlights the considerations evaluated for the choice of the coupling that was implemented between the engine and the BAS

3.4.1. ISG vs. BAS

To couple the electric machine, there are various implementations that can be adopted. The most prominent are belt coupling the electric machine to the engine drive pulley hence a BAS

or coupling the electric machine between the engine flywheel and the transmission hence an

Integrated Starter Generator (ISG). If considered in initial vehicle design, the ISG presents better packaging and space utilization and gets rid of belts that are subject to multiple dynamics, lower efficiencies and belt wear over time. The OSU vehicle however is based off a stock 2016 Camaro that wasn’t designed to have an ISG. Fitting an ISG would necessitate multiple modifications to the engine, engine cradle and transmission to accommodate the electric machine in this location. This coupled with the fact that the EcoCAR competition has strict guidelines regarding modification to the vehicle chassis drove the team to opt for a belt coupling. The BAS option was adopted and modifications only needed to be made to the engine drive pulley. This was also boosted by the fact that there are no other accessories coupled to the engine drive pulley. The team adopted a HV DC/DC converter to take the place of a conventional alternator and a High Voltage Air Conditioning (HVAC) compressor. The vehicle features electric water pumps and power steering thus the only component coupled to the engine drive pulley is the BAS.

3.4.2. Belt Coupling

The belt coupling adopted for the BAS system involved making modifications to both the engine and BAS pulleys. To match the BAS maximum operational speed to the engine maximum speed, a gear ratio was adopted that would ensure that both components would not over-speed. Table 4 shows the mapping of the engine and BAS to determine the appropriate gearing.

Table 4: BAS System Coupling

Parameter Value Engine redline 6500 rpm BAS Max. Speed 18000 rpm Desired Gear Ratio 2.769 Chosen Gear Ratio 2.727

Based on availability of components, a gear ratio of 2.727 was adopted. This comprised of using Helical Offset Tooth sprockets that were machined and fitted onto the engine and BAS.

These sprockets were chosen because of their high efficiency, minimal slip, high power carrying capabilities and ease of matching belts based off the chosen sprockets.

Figure 13: Engine drive pulley

The engine pulley is a 60-tooth sprocket that is shrink fit onto the engine accessory pulley as shown in Figure 13. The BAS pulley is a 22-tooth sprocket that is locked and keyed to the

BAS output shaft. 28

The BAS is rigidly mounted to the engine and a passive tensioning mechanism is adopted using a turn buckle to adjust the belt tension as desired. Figure 14 shows the coupling of the

BAS and the engine.

Figure 14: BAS – Engine coupling

3.5. Thermal Considerations

The BAS is a high power machine packaged in a form factor like that of a conventional alternator. With this high-power output in such a small form factor, the BAS has a small thermal mass. This implies that the BAS heats up much faster than an equally powered motor of larger size. It was expected that the BAS would heat up significantly during constant operation; the issue becoming more apparent during 0 – 60 acceleration runs where it is run at peak power or during series operation. The electronics coolant loop had to be designed with the capability of rejecting heat produced by the BAS at peak operating conditions. Due to the

small thermal mass, the BAS is placed closest to the radiator in the electronics cooling loop as shown in Figure 15. The BAS is rated for a maximum temperature of 150°�, the HSC code is structured to monitor the BAS temperature and derate performance of the BAS above temperatures of 120°�.

Figure 15: Electronics Cooling Loop

Chapter 4: Inverter Evaluation and Validation

The BAS is a sponsor donated component that wasn’t available with an inverter solution. To that end, a custom inverter solution had to be developed by the team to achieve BAS functionality over the entire region of operation. Two inverter choices were evaluated by the team over Years 2 and 3 of the competition. This section details the two inverter choices that were adopted by the team and the pros and cons of each. It also shows the testing and validation work that was done to achieve BAS functionality with both inverters.

4.1. Infineon HybridKit 2

The Infineon Hybrid Kit 2 was chosen based on its specifications detailed in Table 5 and its modular structure. This inverter is a generic prototype kit developed by Infineon Technologies for rapid prototyping purposes of inverter control.

Table 5: Infineon Hybrid Kit Specifications

Parameter Specification Power 80 kW Peak Voltage 650V Motor Position Interface Encoder, Resolver, Hall sensor DC bus capacitance 500 �� Maximum Temperature 150 degrees C Cooling Liquid cooling

The inverter is comprised of the logic board, gate driver board, IGBT pack and heat sink. This modular construction of the inverter was ideal for making changes to the logic board while maintaining the other aspects of the inverter. The inverter shown in Figure 16 also includes a heat sink connected to the IGBT for liquid cooling.

Figure 16: Infineon HybridKit 2

To systematically achieve BAS functionality, development phases were defined to achieve goals for Year 2. The development phases had corresponding test environments to validate system functionality. The following steps were performed to test the inverter under a myriad of conditions:

- LV setup of the inverter and BAS

- HV setup of the BAS & inverter under no load conditions

- HV setup of BAS & inverter with BAS coupled to the dynamometer

4.1.1. LV System Validation

Before the inverter could be supplied with high voltage to control the BAS, the inverter software had to be restructured to work with the motor and calibrated to work for motor specific parameters like motor pole pairs, motor torque constant, D and Q axis inductances, resolver pole pairs and CAN transceiver configuration.

CAN Configuration and Software Modifications

The CAN controller on the logic board was configured to run at a baud rate of 500 kbps and a CAN database file created to cater for the fix point number format used in the inverter.

Figure 17 shows the setup used for LV calibration and flashing of the inverter. All changes to the inverter control software were made using Tasking VX Toolset and flashing the inverter was done using Infineon’s MemTool. Diagnostics and real time parameter monitoring were done through a serial terminal and a serial based GUI.

Figure 17 Inverter LV calibration setup

Analog inputs for the current sensors and thermistors were configured to accurately read currents and motor temperature.

Circuitry Modifications

The circuitry of the inverter was designed for compatibility with a resolver with a transformation ratio of 1. Since the resolver in the BAS has a transformation ratio of 0.2, the resolver excitation buffer circuitry on the inverter was adjusted to produce a gain of magnitude

5. This was achieved using three, 5 kΩ trim potentiometers soldered onto the logic board of the inverter and tuned to achieve the desired amplifier gain. A dual channel oscilloscope was used to verify the excitation, cosine and sine differential signals at the inverter and ensure that they were within the valid ranges for the inverter’s resolver to digital converter; AD2S1200.

Once the LV circuitry had been validated the next step was to validate the HV system

4.1.2. HV System Validation

Circuitry Modifications

The major circuitry modifications on the HV system were related to appropriate sizing of bus bars and integration of current transducers to be used in control of the motor. The current transducers and bus bars were chosen based on the maximum current expected in the BAS

(approximately 150 �). Appropriate insulation was adopted using appropriately rated stands and insulating material to ensure safe integration. Figure 18 shows the final inverter packaging showing both LV and HV connections.

Figure 18: Inverter packaging detailing HV connections

HV Testing

HV tests were carried out using the setup shown in Figure 19.

Figure 19: HV Test Setup

The goal of the HV setup was to validate the inverter startup/shutdown process, motor enabling sequence, validate torque production, evaluate system efficiencies and validate the thermal performance. To achieve this, the instrumentation listed in Table 6 was used

Table 6: Instrumentation used for HV testing

Component Measured variables Dynamometer Speed, torque, mechanical power

Inverter Speed, Torque, temperatures, Currents, �, �, � Current transducer � Belt coupling - dSPACE MABx HSC used to control the inverter Thermistor Motor temperature

AV900 �, � & power

The tests carried out on the system and the results are detailed in the inverter control section.

4.1.3. Inverter Enclosure Design

To package the inverter for safe integration into the vehicle, an enclosure had to be designed for the vehicle. This included designing for coolant connections, HV and LV electrical interface connections, servicing while meeting space claim constraints within the vehicle.

Figure 20 shows the integrated inverter inside the vehicle

Figure 20: Packaged inverter fully integrated in-vehicle

4.1.4. Inverter Control

A controller based on Field Oriented Control was implemented. The inverter was operated in

Torque control mode. To achieve speed control of the BAS, a speed-based PI feedback

controller was wrapped around the Torque request. Control of the inverter is done over CAN with the BAS providing motor speed, position and temperature information to the inverter via resolver and thermistor connections. The torque control input parameters are the � and � current requests. Current map based lookup tables were implemented in the HSC to convert torque requests based on BAS speed to the appropriate � and � requests. The structure of the

FOC implemented in the BAS is as shown in Figure 21

Figure 21: Control implemented for BAS inverter

With the control structure above, the BAS was run in motoring operation to validate torque production under steady state and transient conditions.

Steady State Conditions

Torque production was validated at steady state conditions at various speeds and feedback � and � were compared against current maps to validate the performance of the inverter control. 38

Figure 22 shows the performance of the system at a steady state condition of 5 Nm, 1300 rpm.

The commanded currents closely match the feedback currents which validates the inverter performance within this region.

Figure 22: Controller performance at a steady state condition of 5Nm at 1300 rpm

Transient Conditions

Torque production was validated during transients to validate how the current controllers in the inverter functioned under transient conditions and feedback � and � were compared against current maps to validate the performance of the controller. Figure 23 shows the

performance of the system during transient from 5 Nm to 10 Nm at a speed of 1300 rpm. The commanded currents closely match the feedback currents which validates the inverter performance within this region

Figure 23: Controller performance during transient operation (5Nm, 1300 rpm to 10Nm, 1300 rpm)

Higher Region of Operation

To realize faster engine startup times, a high torque output is desired so validation of the controller in the higher torque region of operation was explored. Figure 24 shows the response of the system in the higher torque region of operation at a torque of 20Nm. The current

controllers were characteristic of multiple ripples to meet the desired torque request. There were significant deviations between the commanded and feedback currents

Figure 24: Higher Torque region of operation

Analysis

As shown in Figure 25, performance of the system in the continuous region of operation at low speeds validated the controller. However, the current controllers were not able to meet the required torque in the higher torque region of operation at the required currents. This

implied lower system efficiencies and unstable current controllers which posed risk of potential to the inverter IGBTs and gate driver board.

Figure 25: Analysis of inverter performance

The implication of this is that the BAS was validated in a limited region of operation i.e. up to 18Nm and 3000 rpm. To be able to meet Year 3 goals of full BAS system functionality, another inverter was evaluated which is detailed in the next section.

4.2. Rinehart PM100DX

Unlike the Infineon HybridKit 2 which required extensive controls development, packaging and validation, a prepackaged inverter solution was adopted that required only controls

developments and calibration in collaboration with a third-party supplier. Figure 26 shows the second inverter that was adopted for BAS control.

Figure 26: Rinehart PM100DX

The technical specifications of the inverter shown in Table 7 ensured that the inverter can be used to control the BAS.

Table 7: PM100DX Specification

Parameter Specification Power 100 kW Peak Voltage 400V, 400V (over voltage) Motor Position Interface Encoder, Resolver, Hall sensor DC bus capacitance 440 �� Maximum Temperature 95 degrees C Cooling Liquid cooling

4.2.1. Inverter Calibration

This inverter had not been configured to work with the BAS and extensive calibration was done at the manufacturer’s facility to validate control of the BAS with this inverter. Despite the relatively high cost associated with this, the calibration efforts carried out by Rinehart

Motion Systems provided the team with an inverter solution that could be used to validate the

BAS along its entire performance range.

4.2.2. Performance Validation

After the initial calibration work done by Rinehart, there was need to calibrate the system to match the desired performance as stipulated by simulation data. This was done on a dynamometer using a similar setup as was used with the Infineon inverter with access to the inverter EEPROM to adjust parameters via a serial interface to match the desired performance.

Steady state testing was done in both motoring and generating mode to validate the BAS system performance up to 13000 rpm. The limitation on the validation was the maximum speed the dynamometer could be taken to before significant vibrations occurred. Figure 27 show the torque speed curve that was derived from experimental data and the corresponding efficiencies achieved. The experimental data torque-speed curve is used in the HSC controls code for torque saturation since it is depictive of the actual torque output of the BAS.

Figure 27: Experimental data torque-speed curve

4.2.3. Thermal Validation

Owing to the small thermal mas of the BAS, it was expected that the BAS would heat up significantly during constant operation; the issue becoming more apparent during 0 – 60 acceleration runs where it is run at peak power or during series operation. To that end, tests were carried out to validate BAS temperature variations series mode on a dynamometer. The variations were monitored for both steady state operation and transient operation

Steady State Testing

This involved testing the BAS under steady state conditions within the continuous region of operation with an end goal of monitoring the temperatures and currents to ensure that they are within bounds. This was used to validate the continuous region of operation where the BAS could be operated constantly without triggering over temperature faults. Figure 28 shows the various parameters evaluated at 30Nm and 3600 rpm.

Figure 28: Steady state BAS testing at 30Nm, 3600 rpm

This test point corresponds to the most efficient region on the engine where the BAS would be operated mostly during series mode of operation. The temperatures levelled out at around

80°� which is well below the maximum BAS temperature of 150°�. These tests were performed along the entire continuous region of operation of the BAS to validate that the BAS maintained a steady state temperature along the entire continuous region of operation.

Transient Operation

To quantify the thermal performance of the BAS at peak regions, the BAS was run in series mode at full power conditions and the temperature rise was monitored to determine how long the BAS could be operated at peak power before significant temperature rise occurred. Figure

29 shows the various parameters when the BAS is moved from a steady state operating point to a peak region of operation. The tests were performed for various test points from steady state to peak region of operation at various speeds.

In the peak region of operation, the temperature rise is much higher and the efficiency of the

BAS gradually decreases as more heat is generated instead of useful work. This testing fed into the HSC controls development to derate BAS torque based on the region of operation and the BAS temperature.

Figure 29: BAS Peak region testing from 30Nm at 3000 rpm to 46Nm at 5500 rpm

It is worth noting that the cooling system used in the dynamometer was more efficient that the one implemented in the vehicle since it used a fresh supply of cold water from a tap.

Nonetheless the electronics cooling loop implemented in-vehicle was designed with capacity to reject heat produced by the BAS and BAS inverter and this was validated through vehicle level testing.

4.3. BAS System Technical Specification

The PM100DX, capable of producing peak power of 100kW, although oversized for the application was the preferred inverter of choice and based on the testing carried out, Table 8 outlines the overall technical specifications of the BAS system.

Table 8: BAS System Specification

Component Manufacturer, model Technical specifications and type Electric Denso, IPM 32 kW Pk. power, 12 kW Cont. power machine 60 Nm peak torque 18000 rpm Max speed 150 Arms Max current Inverter Rinehart PM100DX 100 kW Pk. power 400 V Max. voltage 350 Arms Max. current Engine 2.0L GDI I4 E85 119 kW Pk. power 198 Nm @ 4450 rpm red line 6500 rpm idle speed 600 rpm Belt coupling Belt and sprocket 60 tooth sprocket in place of the engine accessory drive pulley 22 tooth sprocket attached to motor drive shaft Transmission ratio 2.727:1 ESS A123 Systems, Li-ion 18.9 kWh 340 VDC

Chapter 5: System Modeling

To this point, the model used by the team for the BAS system is based on quasi-static approximations using lookup tables and a simple gear ratio to model the belt transmission.

For energy analysis, this model is sufficient but for implementation of a robust engine start/stop controller, a higher fidelity model that accounts for the dynamics of the BAS, engine and belt transmission needed to be developed.

Figure 30: BAS system model overview

The dynamics of the BAS system are a result of the interaction between the BAS, engine and belt transmission. To that end, a model with the structure shown in Figure 30 was developed in MATLAB/Simulink. This model will be further calibrated in Year 4 to develop a robust engine start/stop controller.

5.1. BAS Model

The dynamics of the BAS are fast compared to the dynamics of the engine at idle speeds such that the BAS is modelled using quasi-static approximation. This is achieved using steady state maps provided by the manufacturer.

Figure 31: BAS torque-speed curve

These maps saturate the BAS torque output based on the BAS speed. To more accurately model the physical response of the BAS, a rate transition block is added to account for the rate of change of torque in the BAS torque output. The rate limit programmed in the BAS inverter EEPROM parameters is 5Nm/3ms which allows for fast torque change while respecting inverter switching limits. Figure 31 shows the maximum torque curves of the BAS that are used to saturate the BAS torque command.

5.2. Engine model

A mean value model of the engine would not provide a sufficient representation of the transient dynamics experienced by the engine during an engine start or stop. To that end, a higher resolution engine model in the crank angle domain is developed. The engine is modeled with the crankshaft angle, � as the independent variable. To reduce the computational requirements of the model, several assumptions are made and these will be highlighted. These simplify the development of the model while maintaining the core dynamics that represent engine operation during startup. The engine model is divided into 5 major subsystems i.e.

Crankshaft Kinematics, Indicated Torque, Inertial Torque, Friction Torque, and the Thermal

Model.

5.2.1. Crankshaft Kinematics

The crankshaft kinematics are modeled from the crank slider mechanism as discussed in [17].

The crank slider mechanism is shown in Figure 32. [18]

Figure 32: Crank slider mechanism [18]

The piston displacement, s, is defined by equation (3)

1 � � = � 1 − cos � + 1 − 1 − � sin � 3 �

The piston velocity in the crank angle domain, � is defined by equation (4)

�� sin � cos � � � = = � sin � + 4 �� 1 − � sin �

The piston acceleration, � is defined by equation (5)

� 1 − � sin � + � cos � cos � − � sin � 1 − � sin � � � = = 5 1 − � sin �

Using the crank slider mechanism geometry, the equations representing the instantaneous cylinder volume and the derivative of volume can be expressed as

�� = � + � � 6 4

�� = � � 7 �� 4

� sin � cos � � � = sin � + 8 1 − � sin �

Where � denotes the clearance volume which is calculated with equation (9)

� � = 9 � − 1

� is the compression ration of the engine and � is the swept volume.

5.2.2. Indicated Torque

A crank angle based approach is adopted to develop a single zone thermodynamic model i.e. temperature and pressure are uniform within the control volume. This model predicts the indicated torque and in-cylinder pressure. With regards to developing an engine model that represents the dynamics of the engine for engine start/stop, the major region of the interest is the period between Intake Valve Closing (IVC) and Exhaust Valve Opening (EVO). This region corresponds to the highest compression torques that will be experienced by the engine.

Some of the assumptions employed to simplify the modeling are:

• No leakage from the cylinder

• Temperature and pressure are uniform within the control volume

• The phase between IVC and EVO is considered

• During one engine cycle, the engine speed, � is constant thus � = ��; =

�

• Before IVC, the in-cylinder pressure is equal to the intake manifold pressure

• After EVC, the in-cylinder pressure is equal to the exhaust manifold pressure.

The in-cylinder pressure is given by equation (10)

�� − 1 �� = −� + − 10 ��

The term is representative of rate of heat transfer to the walls of the cylinder. This is modeled using heat transfer given by equation (11)

�� = ℎ� � − � 11 ��

� is the temperature of the cylinder walls, A is the area over which heat transfer occurs and h is the heat transfer coefficient.

� = � + � + �� 12

� is the piston area and � is the area of the cylinder head.

The heat transfer coefficient is modeled using Woschni’s equation [18] [19] 55

� . ℎ = 3.26 ∗ �.�.�. 13 1000

� is the mean piston speed given by the equation � = 2��; where N is the engine speed in rpm.

The term represents the heat generated by the combustion process and is modeled by equation (14)

�� = �� 14 ��

� is the lower heating value of the fuel. The EcoCAR 3 engine is running E85 and thus the lower heating value of E85 fuel is used. � is the mass of fuel injected per engine cycle derived from steady state maps. Before the engine is accelerated to idle speed, the � = 0.

Once the engine is brought up to speed and the ECM initiates fueling, then � ≠ 0.

The term � corresponds to the normalized fuel burning rate (FBR).

�� + 1 � − � = � � ∆ 15 �� ∆� ∆�

Equation (15) is the Weibe function used to model the FBR [18]. Experimental data is used to calibrate the parameters a and m.

Equation (10) is used to calculate the in-cylinder pressure from 1 cylinder. To acquire the in- cylinder pressure for all cylinders, the appropriate phasing is introduced based on the engine firing sequence. The cylinder firing sequence for the OSU EcoCAR 3 engine is 1-3-4-2.

The indicated torque is calculated according to equation (16)

� � = � ∗ � ∗ � � − � ∗ � � 16

The indicated torques from the various cylinders are summed up to get the total indicated torque as seen at the engine crankshaft.

5.2.3. Inertial Torque

The non-linear inertias of the pistons are approximated as an external torque [20], � which is calculated according to equation (17)

� � = �� 17

The inertial force is calculated by using Newton’s second law of motion of the masses while considering the reciprocating motion of the pistons as shown in equation (18).

�� = � + 18 ��

5.2.4. Friction Torque

The model adopted for the friction torque is as proposed in [21] [18] where the engine friction is composed majorly of two terms; one term correlated to engine speed and the second term due to friction between the engine piston rings and the cylinder walls. The first term is a relatively constant term related to damping and the second term varies based on crank position, cylinder pressure and engine oil viscosity.

The engine friction is modeled by equation (19)

� � = �� + �� 19

where � corresponds to the cylinder pressure of each respective cylinder, and � is the oil viscosity.

The oil viscosity is largely dependent on temperature and the relation between the oil viscosity and temperature is approximated using Roeland’s expression [22]. The expression for oil viscosity is given by equation (20)

� = �10 20

where � = 6.31 ∗ 10 and T is the temperature in ℃. Based on SAE 5w-40 oil viscosity tables from [23], an optimization was performed to determine the coefficients �and � as

4.0771 and 1.0723 respectively.

5.2.5. Thermal Model

The major considerations for the thermal model are in-cylinder temperature and the temperature of the engine walls due to friction.

In-cylinder Temperature

The assumption made is that since there are no leakages, the mass in the cylinder remains constant. Taking the derivative of the ideal gas law, an equation that expresses the temperature of the fluid in the cylinder is given by equation (21)

�� 1 �� = � + � 21 ��

During engine starts, as the engine is accelerated to the desired speed set-point, the changes in in-cylinder temperature are primarily due to the pressure changes due to compression of air in the cylinder and not due to combustion.

Engine Temperature

From equation (19), engine friction is highly dependent on engine oil temperature. This is more prevalent in HEVs which are characteristic of multiple engine starts. A model that predicts engine temperature is essential to model the dynamics of engine wall temperature.

During the start events, combustion contributes less to engine oil heating and the most dominant factor is due to friction heating. To that end, a lumped parameter model based on energy balance relationship is adopted that models friction heating and convection cooling.

This is modeled using equation (22)

�� 1 �� = � � − ℎ� � − � 22 ��

� is the temperature of the coolant that can be acquired from interfacing with the ECM.

� is the specific heat capacity of the engine, � is the mass of the engine. The parameters that need to be calibrated are ℎ� and �. This is achieved by running various cold start and hot start tests where the engine is motored by the BAS. The corresponding BAS torque, � are used as inputs to the model to match the engine temperature to experimental data.

5.3. Belt Transmission Model

The belt transmission is modeled based on Lagrange equations that relate the kinetic energy

(T), Rayleigh dissipation function (D), potential energy due to deformation of the belt branches (U) and work done due to the external torques (W) [24]. The belt transmission model is based off Figure 33. The damping coefficient, B and the stiffness constant of the belt, K are considered as lumped parameters of the two branches of the belt with � ≅ 2� and � ≅ 2�.

The parameter K was determined from manufacturer data and testing. The parameter B was approximated based on the material of the belt.

Figure 33: Belt Transmission

The Lagrange equations are:

� �� − + + = ; � = 1,2 23 ��

The virtual work done, W by the motor and engine is represented by the equation 60

�� = �� − �� 24

The Kinetic Energy, T is represented by the equation

1 � = � � + � � 25 2 , ,

The Potential energy, U is represented by the equation

� = � �� − �� 26

The Rayleigh dissipation function, D is defined by the equation

� = � �� − �� 27

The input to the belt transmission model are the torques from the engine and BAS model i.e.

� and �. The outputs from the model are �, � , �, �, �, �

The equations of the model shown in Figure 33 are:

�,� = � + � �� − � � + � �� − � � 22

�,� = � − � � � − �� − � � � − �� 23

5.3.1. Assumptions

• There is no slipping since these are synchronous belts. The unique tooth configuration

of the belts ensures continuous tooth engagement which eliminates slippage [25]

• The mass of the belt is negligible compared to the mass of the pulleys.

• The equivalent inertias of the BAS and Engine are lumped parameters accounting for

the inertias of the respective pulleys.

To validate that the two degree of freedom model adopted is sufficient to model the belt transmission dynamics, experimental data is used to compare the engine speed with BAS equivalent speed as seen from the engine pulley.

Figure 34: Comparison of BAS and Engine Speeds

Figure 34 shows experimental data of the general trend of the BAS speed and engine speed with similar magnitudes and peaks. This implies that the dominant belt dynamics that need to be accounted for is belt stretch thus the 2 DOF model is sufficient to model the belt transmission.

5.4. Model Calibration and Validation

With the assumptions made, the parameters that need to be calibrated and validated are outlined in Table 9. The major parameters that need to be calibrated are the friction coefficients and thermal coefficients which greatly reduces the number of tests that need to be carried out.

Table 9: BAS System Calibration Parameter

Parameter Value

Viscosity parameters � = 4.0771, � = 1.0723 (SAE 5w-40 oil) Belt parameters � = 42.04��/�, � = 40 ��/� Friction coefficients �, � Thermal coefficients ℎ�, � = 4.6 ∗ 10 �/��

5.4.1. Friction Parameter Calibration

To calibrate the friction parameters, the BAS is used to motor the engine from cold start without controlling the ECM to turn on fueling. The motoring is done for about 30s and the coolant temperature, engine speed, BAS torque are recorded. These are fed into the simulator as inputs and the engine speed output is monitored as the output. To calibrate the coefficients, a 2 step process is adopted. The first step considers the first seconds (~3s) of the startup where the effect of temperature on oil viscosity is not as pronounced. The dominant friction term is the constant term that is dependent on engine speed. This step is used to determine the coefficient � using a least squares approximation method. The second step involves feeding the entire profile into the simulator to account for dependence of friction on piston position,

oil viscosity and in-cylinder pressure. With the � coefficient determined, this is used to determine the � coefficient using a least squares approximation

The model is undergoing further calibration and tuning and will be the base model used to develop the engine start/stop controller in Year 4 of the competition.

Chapter 6: Engine Start Control

This chapter details the various control strategies implemented for engine start and evaluation of the performance of the control strategies using metrics of start time, jerk, RMS acceleration and VDV.

6.1. Control Problem Definition

For engine start, the goal is to create a simple but robust controller that starts the engine as fast as possible while minimizing engine speed overshoot. This controller is implemented in the HSC. During engine start/stop events, the variable to be controlled is the engine speed.

The fluctuations in engine speed during engine start/stop events are primarily due to compression events and implementing a controller that minimizes the fluctuation in engine speed is desired. Two major control strategies explored are implemented and evaluated in the next section.

For the purposes of this thesis, engine start time is the performance criteria of the controller and is evaluated as the time before the engine initiates the first fire. This is quantified as the time taken to accelerate the engine to a desired engine speed set-point. The engine speed set- point was chosen to be 1000 rpm. When the engine reaches the engine speed set-point, the fuel relay is energized and the ECM initiates fueling.

6.1.1. Engine Starts

During an engine start, the major control challenge is to minimize engine speed overshoot

� while maintaining fast startup time and reducing the rise time �. Figure 35 shows an engine startup with the parameters � and � indicated. The pulses in the engine speed are primarily due to compression torque

Figure 35: Engine start showing engine speed overshoot

6.1.2. Engine Stops

During an engine stop, the challenge is to minimize engine speed undershoot while bringing the engine to a quick stop. These two parameters are at conflict with each other since achieving

a fast engine stop by absorbing torque using the BAS would increase engine speed undershoot.

The NVH issues related to engine stops are due to the engine going through the chassis resonance as it comes to a stop. Figure 36 shows the engine speed stop profile. Currently, an engine stop is achieved by cutting fuel to the engine by de-energizing the fuel pump relay.

From Figure 36, the engine comes to a halt in about a 1.5s with minimal engine speed overshoot. This is deemed as a sufficient engine stop profile thus more focus is applied to engine startup as opposed to engine stop.

Figure 36: Engine stop showing engine speed undershoot

6.2. Exponential Speed Profiles

To create speed profiles that are used as reference inputs to the controller, exponential speed profiles with adjustable time constants were created. The exponential engine speed profiles are defined by equation (24) [26]

� � = � ∗ 1 − 24 �

Where � is the set-point that the engine is to be accelerated to, � is the length of the start profile and � is the time constant. � is set to 1000 rpm. To achieve engine start profiles, the transpose of equation (24) is calculated and this produces the desired engine start profile. Figure 37 shows the various engine start profiles corresponding to various time constants. The length of the start profile was chosen to be 1.5s and the engine start times range from 0.2s to 1.2s. Start profiles that correspond to engine starts under 1s were considered thus time constants in the range of 50ms to 200ms were considered for further controller development. The lower time constants correspond to faster engine start times but high � and �. Higher time constants on the other hand correspond to slower engine start times but low � and �. An objective function needs to be created to find the time constant which provides an optimal solution.

Figure 37: Exponential engine start profiles

To achieve the desired engine stop profiles, equation (24) is transposed and subtracted from

� such that the end point of the speed trace is zero. Figure 38 shows engine stop profiles at various time constants. As mentioned earlier, since the engine stop profile due to cutting fuel from the engine produces a fast engine stop with minimal engine speed undershoot, the focus of the controller is shifted to optimizing for engine starts.

Figure 38: Exponential engine stop profiles

6.3. Objective Function

To determine the optimal reference exponential speed profile, an objective function was created that minimizes the following parameters �, �, ��, �.

The objective function is defined as

�� = + � + � + � 25 � � ��

Where the coefficients �, �, �, � are weights for the different criteria. For an initial analysis, the weights are considered equivalent thus � = � = � = � = 0.25. These weights can be adjusted depending on the desired goals of the engine start controller under development.

Since the goal is to minimize all the parameters, the values � = min (�), � =

min(�), �� = min(��) and � = min(�) for the various time constants considered in the range 50ms to 200ms.

The various start profiles are evaluated for different time constants and minimum values that are used in the objective function are shown in Table 10.

Table 10: Minimum values for optimization function

Parameter Value

� 5.6148

� 1.5

�� 10.28

� 0.2

Figure 39 shows the variation of the various metrics (�, ��, � and �) with choice of time constant �. The objective function in equation (25) is then evaluated at each value of

� to determine the optimal engine start profile that minimizes the objective function. This optimal start profile is used as a reference input speed profile to the closed loop controller.

The optimal reference engine start profile is found to be one with a time constant of 92 �� which corresponds to a � = 0.36� which is within our requirement of 0.25s to 0.4s as stipulated in [16].

Figure 39: Variation of metrics for various time constants

Table 11 shows the parameters evaluated for the optimal reference profile that minimizes the objective function.

Table 11: Optimal reference engine start profile parameters

Parameter Value

� 8.2754

� 1.5 �� 18.3903 � 0.36

The maximum jerk is equal to the lowest possible �. There are slight increases in � and

� and significantly higher increase in ��. Figure 40 shows the variation of the cost function with � with the minimum cost corresponding to a time constant of 92ms.

Figure 40: Cost vs. � [��]

With the optimal � determined, equation (24) is used to determine the optimal engine start profile shown in Figure 41. This profile is used as an input to the closed loop controller.

Figure 41: Optimal reference engine start profile

6.4. Open Loop Engine Start Controller

With the goal of developing a simple but robust controller, the first control strategy evaluated is the open loop controller where a pulse BAS torque is applied. The open loop engine start/stop is achieved by requesting a constant torque command from the BAS controller for a short time period. After the pulse BAS torque profile, a PI controller is used to ensure that the engine speed is maintained to a set-point; 1000 rpm is the considered set-point. Once the engine has maintained this speed for a calibrated period of time, the fuel pump relay is energized and the ECM initiates fueling converting the engine state from Cranking to Run.

With the engine in a Run state, the HSC commands zero torque from the BAS. This is the simplest engine start controller that can be easily implemented and this is used as a baseline for comparison with the closed loop controller. The output variable that we wish to control is the engine speed. During engine cranking, the encoder that determines the engine speed isn’t reliable because ECM isn’t fully powered up. The BAS speed reported by the BAS inverter is used to determine engine speed with the appropriate gear multiplication factored in.

Figure 42: Open loop controller response

Figure 42 shows an engine start profile using an open loop start with the fuel pump relay de- energized and the ECM commands onset start fueling. After the pulse BAS torque profile for

0.4s, a PI controller controls the BAS torque command and maintains the engine speed at the set-point until fueling is commanded. The HSC commands negative torque from the BAS to account for the overshoot in engine speed due to the pulse torque profile. The PI then provides positive torque output as shown in Figure 42 to overcome the compression, friction and inertial torque of the engine to maintain engine speed at the set-point. The overshoot in engine speed, � is ~230 ��. The performance metrics are applied to the open loop controller to evaluate its response and the results are shown in Table 12.

Table 12: Open Loop controller parameters

Parameter Value

� 11.85

� 0.59 �� 11.67

� 0.33

Although the rise time is within the requirement of 0.25 – 0.4s, there is a high overshoot in engine speed and a high �. There is a 110% increase in � from the lowest possible value from the exponential speed profile. The �� is close to the optimal value from the exponential speed profile. To mitigate the engine speed overshoot and high �, a closed loop controller is explored. The open loop controller is used as a baseline to evaluate the performance of the closed loop controller that is discussed in the next section.

6.5. Closed Loop Engine Start Controller

Unlike the open loop engine start controller, the closed loop engine start controller uses the engine speed feedback as a control input. The controller has the structure shown in Figure 43 which comprises of a feedback and a feedforward component.

Figure 43: Closed loop controller structure

The feedback controller comprises of a PI controller that uses engine feedback speed to provide a torque request. The feedforward component is designed to reduce the burden on the

PI controller by predicting the engine torque components (friction torque, inertial torque or compression torque) based on �, � or both. For initial investigation, the feedforward component is employed as a friction torque lookup table based on manufacturer data that predicts friction torque based on engine speed. The output of the FF and FB controller are summed together and comprise the BAS torque request command. The controller is

implemented in the HSC logic and adopts the structure shown in Figure 43. The response of the controller showing the engine speed and BAS torque is shown in Figure 44.

Figure 44: Closed loop controller response

Unlike the open loop controller that employs a pulse torque profile, the closed loop controller seeks to minimize the overshoot in engine speed while minimizing the engine startup time.

As seen in Figure 44, there is no negative BAS torque applied to mitigate for engine speed overshoot. The closed loop controller is evaluated and the resultant parameters are shown in

Table 13.

Table 13: Closed loop controller parameters

Parameter Value

� 8.02

� 1.6 �� 17.18 � 0.849

From Table 13, the controller reduces the � and � at the expense of higher rise time. Compared with the open loop controller response, there is minimal �, a 32.3% reduction in � albeit an increase of 0.5s in �. The large increase in � is primarily due to torque saturation of the BAS torque output to maintain BAS operation within the continuous region of operation and a rate limit block employed in the HSC logic to limit the rate of change of BAS torque output. To mitigate this with a goal of further reducing �, the BAS torque saturation limit is increased to and the rate limiter is removed and employed only in the BAS inverter EEPROM parameters.

The discrepancies between the experimental data and the exponential profile data is primarily due to engine dynamics (friction, compression and inertia) that are best approximated with the dynamic engine development that is under calibration. This model will be used in Year 4 to predict engine dynamics and develop a more robust engine start controller that meets the desired specifications. The next section explored the performance of the controller with a higher torque saturation limit and no rate limiter implemented in the HSC logic.

6.5.1. Tuned Closed Loop Controller

To achieve a faster rise time, higher torque output from the BAS is explored to achieve an engine start within the required time while minimizing �. The rate transition is also adjusted to ensure that the requested BAS torque from the controller is similar to the BAS torque command that is sent to the inverter. Figure 45 shows the tuned response of the controller which achieves a higher BAS torque output command and faster engine start time.

Figure 45: Closed Loop controller tuned response

The tuned controller is also evaluated on the same metrics used to evaluate the open loop controller and the un-tuned closed loop controller. According to Table 14, the tuned controller is able of reducing all the parameters �, �, �� . The rise time � is reduced to 0.53s which is close to the design parameter of 0.25 – 0.4s. The � also reduces by 33.4% compared to the open loop controller and performs 1.6% better than the untuned closed loop controller. The �� reduces by 29.3% compared to the untuned closed loop controller.

Table 14: Tuned closed loop controller parameters

Parameter Value

� 7.89

� 1.097 �� 12.15 � 0.53

The tuned closed loop controller performs better with less �, � and ��. Despite the � being slightly over the 0.4s, it is deemed sufficient to start the engine while maintaining the performance metrics of NVH low. The next step is validation of the closed loop controller for various engine temperatures. This is primarily because engine friction is a dominant term in engine starts and it varies with temperature. The situation is of paramount importance in

HEVs which are characterized by multiple engine starts/stops during a given drive cycle thus it is useful to validate the engine start controller for various starts at different engine temperatures.

6.5.2. Various Engine Starts

The tuned CL controller is evaluated for various engine starting temperatures. This is to range from cold starts to hot starts to verify how the controller performs under different engine starting operations. Figure 46 shows the evaluation of engine starts profiles for temperatures of 23°�, 36°� �� 83°�.

Figure 46: Engine starts for various engine temperatures

Table 15 shows that the controller performs well despite the changes in engine friction torque due to temperature. � of ~0.6� is observed while � and � average around 10.18 and

0.74 respectively showing that this controller is robust enough even under various engine temperature conditions

Table 15: Various engine starts - parameter evaluation

�� . �� 23°� 10.579 0.77 16.935 0.59 36°� 9.657 0.819 14.372 0.609 83°� 10.311 0.643 12.825 0.584

6.6. Summary

This section has detailed the methodology adopted to develop a simple and robust engine start controller to start the engine with minimal overshoot, as quickly as possible while maintaining the performance metrics of �, � and �� within values close to the optimal performance expected from the exponential speed profile.

To further improve the performance of the controller, the FF component of the controller needs to be adjusted to cater for prediction of compression torque and inertial torque. This is dependent on the dynamic model under development that will be implemented and evaluated in Year 4 of the competition.

Chapter 7: Conclusions and Future Work

This chapter summarizes the work that has been done and sets the platform for future work to improve BAS system functionality.

7.1. Work Done

This thesis has detailed the work done regarding the BAS system. High level vehicle requirements developed by the team in Year 1 drove the architecture selection and preliminary

VTS targets. A major system component to achieve these VTS targets is the BAS system which aids in engine start/stop functionality, mild series mode, torque assist mode and speed matching to help improve shifting.

The versatility of the BAS that the team chose coupled with the fact that the BAS wasn’t donated to the team with an inverter solution, this system need to be carefully designed and validated to realize full component functionality in Years 2 – 4 of the competition. This thesis detailed the work done with regards to:

• Using the vehicle level requirements to determine system and component level

requirements that led to design specifications for the BAS system. The design

specifications ranged from electrical, mechanical, performance to thermal design

requirements.

• Evaluation of two inverter choices adopted by the team and the testing, validation and

packaging work done to realize BAS system functionality. The Infineon HybridKit 2

and the PM100 inverters were packaged, calibrated and the BAS functionality with

both inverters was evaluated.

• Methodology adopted to develop a model for the BAS system capable of predicting

engine, BAS and belt dynamics during engine starts and stops. This model will be

further calibrated and used for controls development in Year 4 of the competition to

implement and optimize engine start-stop functionality.

• Evaluation of two engine start control strategies and optimization of the controller to

minimize engine speed overshoot while maintaining acceptable engine start times. The

closed loop controller was then evaluated for various engine temperatures to evaluate

the robustness of the controller.

7.2. Future Work

The work done in Years 2 and 3 of the competition has set the groundwork such that future work on the BAS system is promoted to vehicle level testing as opposed to a component and/or systems level. To further utilize the BAS system to meet the team VTS targets, work to be done in Year 4 of the completion includes:

• Calibration of the dynamic engine model to validate that the model accurately predicts

the dynamics of the engine, BAS and belt transmission during engine starts and stops.

• Validation of the calibrated model by comparing it with experimental data collected

both from chassis dynamometer and on road vehicle tests.

• Using the calibrated model and inverting it to alter the FF component of the CL

controller such that the controller can predict compression and inertial torque based

on �, � and in-cylinder pressure. This has the effect of reducing the ripple in

engine speed during engine starts and thereby even further minimizing �, � and

�� while maintaining fast engine start times

• Implementing a robust engine start-stop controller that considers frequency of engine

starts, emissions and fuel consumption as part of the objective function used to

evaluate controller performance.

• Using the BAS system for launch control and speed matching and optimizing for

drivability. This is highly dependent on extensive vehicle testing and the shifting

control strategy that will be implemented in Year 4 of the competition.

The goal is to achieve full BAS system functionality and application at the end of Year 4 competition to meet the team VTS targets.

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