Hybrid Electric Vehicle System Modeling and Control E-Book

Wei Liu

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: Automotive Series
• Sprache: Englisch
• Veröffentlichungsjahr: 2017

Seitenzahl: 693

Beschreibung

This new edition includes approximately 30% new materials covering the following information that has been added to this important work: * extends the contents on Li-ion batteries detailing the positive and negative electrodes and characteristics and other components including binder, electrolyte, separator and foils, and the structure of Li-ion battery cell. Nickel-cadmium batteries are deleted. * adds a new section presenting the modelling of multi-mode electrically variable transmission, which gradually became the main structure of the hybrid power-train during the last 5 years. * newly added chapter on noise and vibration of hybrid vehicles introduces the basics of vibration and noise issues associated with power-train, driveline and vehicle vibrations, and addresses control solutions to reduce the noise and vibration levels. Chapter 10 (chapter 9 of the first edition) is extended by presenting EPA and UN newly required test drive schedules and test procedures for hybrid electric mileage calculation for window sticker considerations. In addition to the above major changes in this second edition, adaptive charging sustaining point determination method is presented to have a plug-in hybrid electric vehicle with optimum performance.

Leseprobe

Table of Contents

Cover

Title Page

Preface

List of Abbreviations

Nomenclature

1 Introduction

1.1 Classification of Hybrid Electric Vehicles

1.2 General Architectures of Hybrid Electric Vehicles

1.3 Typical Layouts of the Parallel Hybrid Electric Propulsion System

1.4 Hybrid Electric Vehicle System Components

1.5 Hybrid Electric Vehicle System Analysis

1.6 Controls of Hybrid Electric Vehicles

References

2 Basic Components of Hybrid Electric Vehicles

2.1 The Prime Mover

2.2 Electric Motor with a DC–DC Converter and a DC–AC Inverter

2.3 Energy Storage System

2.4 Transmission System in Hybrid Electric Vehicles

References

3 Hybrid Electric Vehicle System Modeling

3.1 Modeling of an Internal Combustion Engine

3.2 Modeling of an Electric Motor

3.3 Modeling of the Battery System

3.4 Modeling of the Transmission System

3.5 Modeling of a Multi‐mode Electrically Variable Transmission

3.6 Lever Analogy as a Tool for ECVT Kinematic Analysis

3.7 Modeling of the Vehicle Body

3.8 Modeling of the Final Drive and Wheel

3.9 PID‐based Driver Model

References

4 Power Electronics and Electric Motor Drives in Hybrid Electric Vehicles

4.1 Basic Power Electronic Devices

4.2 DC–DC Converters

4.3 DC–AC Inverters

4.4 Electric Motor Drives

4.5 Plug‐in Battery Charger Design

References

5 Energy Storage System Modeling and Control

5.1 Introduction

5.2 Methods of Determining the State of Charge

5.3 Estimation of Battery Power Availability

5.4 Battery Life Prediction

5.5 Cell Balancing

5.6 Estimation of Cell Core Temperature

5.7 Battery System Efficiency

References

6 Energy Management Strategies for Hybrid Electric Vehicles

6.1 Introduction

6.2 Rule‐based Energy Management Strategy

6.3 Fuzzy‐logic‐based Energy Management Strategy

6.4 Determination of the Optimal ICE Operational Points of Hybrid Electric Vehicles

6.5 Cost‐function‐based Optimal Energy Management Strategy

6.6 Optimal Energy Management Strategy Incorporated with Cycle Pattern Recognition

References

7 Other Hybrid Electric Vehicle Control Problems

7.1 Basics of Internal Combustion Engine Control

7.2 Engine Torque Fluctuation Dumping Control Through the Electric Motor

7.3 High‐voltage Bus Spike Control

7.4 Thermal Control of an HEV Battery System

7.5 HEV/EV Traction Motor Control

7.6 Active Suspension Control in HEV/EV Systems

7.7 Adaptive Charge‐sustaining Setpoint and Adaptive Recharge SOC Determination for PHEVs

7.8 Online Tuning Strategy of the SOC Lower Bound in CS Operational Mode

7.9 PHEV Battery CS‐operation Nominal SOC Setpoint Online Tuning

References

8 Plug‐in Charging Characteristics, Algorithm, and Impact on the Power Distribution System

8.1 Introduction

8.2 Plug‐in Hybrid Vehicle Battery System and Charging Characteristics

8.3 Battery Life and Safety Impacts of Plug‐in Charging Current and Temperature

8.4 Plug‐in Charging Control

8.5 Impacts of Plug‐in Charging on the Electricity Network

8.6 Optimal Plug‐in Charging Strategy

References

9 Hybrid Electric Vehicle Vibration, Noise, and Control

9.1 Basics of Noise and Vibration

9.2 General Description of Noise, Vibration, and Control in Hybrid Electric Vehicles

References

10 Hybrid Electric Vehicle Design and Performance Analysis

10.1 Hybrid Electric Vehicle Simulation System

10.2 Typical Test Driving Cycles

10.3 Sizing Components and Vehicle Performance Analysis

10.4 Fuel Economy, Emissions, and Electric Mileage Calculation

References

Appendix A: System Identification, State and Parameter Estimation Techniques

A.1 Dynamic System and Mathematical Models

A.2 Parameter Estimation for Dynamic Systems

A.3 State Estimation for Dynamic Systems

A.4 Joint State and Parameter Estimation for Dynamic Systems

A.5 Enhancement of Numerical Stability in Parameter and State Estimation

A.6 Procedure of Modeling and Parameter Identification

References

Appendix B: Advanced Dynamic System Control Techniques

B.1 Pole Placement in Control Systems

B.2 Optimal Control

B.3 Stochastic and Adaptive Control

B.4 Fault‐tolerant Control

References

Index

End User License Agreement

List of Tables

Chapter 01

Table 1.1 The main features and capabilities of various hybrid electric vehicles

Chapter 02

Table 2.1 Basic technical requirements for a lead–acid cell in HEV/EV applications

Table 2.2 Basic technical requirements for an NiMH cell in HEV/EV applications

Table 2.3 Characteristics of common Li‐ion battery cathode materials

Table 2.4 Advantages and disadvantages of common Li‐ion batteries with different cathode materials

Table 2.5 Basic technical requirements for a Li‐ion cell in HEV/EV applications

Chapter 03

Table 3.1 The fuel consumption mapping data of a 1.8 L diesel engine (mL/s)

Table 3.2 The efficiency (%) of the motor/generator set

Table 3.3 Battery model parameters of a 4.4 Ahr battery system at 25 °C at the beginning of the system’s life

Table 3.4 The states of the clutches and the power split device in the hybrid vehicle system illustrated in Fig. 3.25

Table 3.5 Some operational speeds of the given ECVT

Chapter 04

Table 4.1 States and output voltages of the voltage source three‐phase inverter

Table 4.2 States of Hall sensors and power switches for a motor rotating in a clockwise direction

Table 4.3 States of Hall sensors and power switches for a motor rotating in a counter‐clockwise direction

Table 4.4 Typical technical specification parameters for BLDC motors in HEV/EV applications

Chapter 05

Table 5.1 The SOC (%) look‐up chart indexed by

V

oc

(V) and temperature (°C) of a system with 32 4.5 Ahr Li‐ion batteries

Table 5.2 Extracted model parameters based on HPPC test at 50% SOC and 25 °C for a 5.3 Ahr Li‐ion cell

Table 5.3 Operational limits of the 5.3 Ahr Li‐ion battery cell at 50% SOC and 25 °C

Table 5.4 Calculated power availabilities using different methods of the example cell at 50% SOC and 25 °C

Table 5.5 Cycle life test result for a Li‐ion battery at 25 °C for plug‐in hybrid vehicle application

Table 5.6 Performed cycle number for Example 5.7 over the usage profile given in Example 5.5

Table 5.7 Vehicle operation profile

Table 5.8 Efficiencies of a Li‐ion battery system for HEV application

Chapter 06

Table 6.1 The values of the characteristic function in crisp sets and the membership function in fuzzy sets

Table 6.2 Fuzzy logic rules of an energy management strategy for an HEV

Table 6.3 Formularized fuzzy logic rules

Table 6.4 Corresponding engine‐mapping data for optimizing the operational points

Table 6.5 Values of objective function one (

J

1

) at each power requirement point

Table 6.6 Evaluated results in the period of 10 ms

Chapter 07

Table 7.1 BOL Li‐ion battery pack electrical equivalent circuit model parameters

Chapter 08

Table 8.1 Maximal plug‐in charge current of a PHEV battery pack

Table 8.2 Example of the calculated battery SOC and temperature corresponding to different charging power during the

i

th charging period

Table 8.3 Operational efficiency of the given plug‐in charger

Table 8.4 Charging efficiency of the given battery system

Table 8.5 Given price of electrical energy

Table 8.6 Calculated charging schedule

Chapter 09

Table 9.1 Sound velocities and wavelengths in different materials commonly used in road vehicles

Table 9.2 Central and approximate cut‐off frequencies (Hz) of one‐octave bands

Table 9.3 Central and approximate cut‐off frequencies (Hz) of one‐third‐octave bands

Table 9.4 Comfort levels for various acceleration levels

Chapter 10

Table 10.1 Summary of the UDDS, HD‐UDDS, FTP‐75, HWFET, and NYCC driving schedules

Table 10.2 Summary of US06, SC03, and LA92 driving schedules

Table 10.3 Summary of the ECE, EUDC, and EUDC‐LP driving schedules

Table 10.4 Summary of WLTP driving schedules

Table 10.5 Typical automatic transmission first and reverse gear launch requirements for drivability

Table 10.6 Typical automatic transmission top gear gradeability requirements

Table 10.7 Vehicle parameters for Example 10.1

Table 10.8 Specification of the selected battery cell

Table 10.9 Key characteristics of the five‐cycle emission and fuel economy tests

Appendix A

Table A.1 Computational results of Example A.4

List of Illustrations

Chapter 01

Figure 1.1 A rear‐wheel‐drive series hybrid electric vehicle layout

Figure 1.2 A rear‐wheel‐drive parallel hybrid electric vehicle layout

Figure 1.3 A rear‐wheel‐drive series–parallel hybrid electric vehicle layout

Figure 1.4 Typical parallel hybrid electrified powertrain arrangements

Figure 1.5 Power flow of a series hybrid electric vehicle

Figure 1.6 Power flow of a parallel hybrid electric vehicle

Figure 1.7 Typical urban cycle energy flows of a conventional powertrain and a hybrid electrified powertrain

Chapter 02

Figure 2.1 Torque/power vs. speed curve of a gasoline engine

Figure 2.2 Fuel consumption contour of a gasoline engine

Figure 2.3 Typical torque/power vs. speed curve of a diesel engine

Figure 2.4 Typical fuel efficiency contour of a diesel engine

Figure 2.5 Working principle of PEM fuel cells

Figure 2.6 Fuel cell voltage vs. current density curve

Figure 2.7 Fuel‐cell‐based prime mover

Figure 2.8 Typical curve of torque/power vs. speed of an induction motor system

Figure 2.9 Efficiency map of an induction motor system

Figure 2.10 Typical curve of torque/power vs. speed of a BLDC motor system

Figure 2.11 Efficiency map of a BLDC motor system

Figure 2.12 Common crystalline structures of cathode materials for Li‐ion batteries.

Figure 2.13 The characteristics of OCV vs SOC of Li‐ion batteries made from different cathode materials

Figure 2.14 1C discharge profiles of Li‐ion batteries made from different electrode materials

Figure 2.15 Main components of a Li‐ion battery. (a) A Li‐ion pouch cell; (b) section A–A view: structure and main components of a Li‐ion cell

Figure 2.16 A simple ECVT schematic diagram

Figure 2.17 Mechanical diagram of an ECVT gear system

Figure 2.18 Section diagram of an ECVT housing

Chapter 03

Figure 3.1 Frictional and compression torque of an internal combustion engine. (a) Static friction torque; (b) Coulomb friction torque; (c) the functional relationship between viscous friction torque and angular velocity; (d) the functional relationship between the compression torque and angular velocity

Figure 3.2 Engine idle speed control principle

Figure 3.3 Typical maximal torque vs. speed curve of a gasoline engine

Figure 3.4 Diagram of the fuel consumption and emissions calculation

Figure 3.5 Engine cranking model

Figure 3.6 Cranking speed response of the engine. (a) The power characteristics of the engine accessory; (b) the cranking speed response of the engine

Figure 3.7 Diagram of engine idle control

Figure 3.8 EPA urban dynamometer driving schedule

Figure 3.9 The power demand on the engine shaft over the EPA urban cycle

Figure 3.10 The set of operational points of the engine

Figure 3.11 Diagram of the electric motor model in propulsion mode

Figure 3.12 Diagram of the electric motor model in regenerative mode

Figure 3.13 US06 drive cycle

Figure 3.14 The electric motor speed over the US06 drive cycle

Figure 3.15 The demand torque on the electric motor driveshaft over the US06 drive cycle

Figure 3.16 The maximal allowable torque of an electric motor

Figure 3.17 The current demand on the high‐voltage bus over the US06 drive cycle

Figure 3.18 Electrochemical operation of a battery cell (dashed lines: discharge flow; dotted lines: charge flow)

Figure 3.19 The electrical circuit equivalent model of a battery

Figure 3.20 (a) Entire HPPC test sequence; (b) the detailed test pulse at each SOC level

Figure 3.21 Hybrid pulse power characterization test

Figure 3.22 The battery test current profile

Figure 3.23 Actual and model‐predicted battery terminal voltages

Figure 3.24 Battery SOC varying range over the battery usage test profile

Figure 3.25 The conceptual architecture of an input split hybrid electric vehicle. (a) The conceptual architecture; (b) a schematic of the planetary gear set

Figure 3.26 Diagram of an automatic transmission model

Figure 3.27 Model diagrams of the power split device with clutches in a hybrid electric vehicle transmission. (a) Clutch control signal is 011; (b) clutch control signal is 101; (c) clutch control signal is 110; (d) clutch control signal is 111

Figure 3.28 A diagram of the torque converter model

Figure 3.29 The model diagram of a gearbox

Figure 3.30 A simple ECVT schematic diagram

Figure 3.31 Curve of ICE operational speed vs. vehicle speed

Figure 3.32 One‐mode ECVT power flow chart under a low power demand operational condition (highway cruising)

Figure 3.33 One‐mode ECVT power flow chart under a high power demand operational condition (WOT acceleration)

Figure 3.34 A two‐mode EVT schematic diagram

Figure 3.35 Schematic cross‐section of the two‐mode ECVT

Figure 3.36 Compound planetary gear set with double planetary gears

Figure 3.37 Optimal operation curves of the ICE under low and high power conditions

Figure 3.38 Operational power of two‐mode ECVT under low power conditions

Figure 3.39 Operational power of two‐mode ECVT under high power conditions

Figure 3.40 Operational speed of two‐mode ECVT under low power conditions

Figure 3.41 Operational speed of two‐mode ECVT under high power conditions

Figure 3.42 Simple planetary gear set lever analogy diagram. (a) Stick diagram, (b) Lever diagram case A, (c) Lever diagram case B

Figure 3.43 Compound planetary gear set lever analogy diagram. (a) Stick diagram, (b) Lever diagram case A, (c) Lever diagram case B

Figure 3.44 Diagram of two interconnected planetary gear sets

Figure 3.45 Lever analogy diagram for two interconnected planetary gear sets. (a) Lever diagram for procedure 1; (b) lever diagram for procedure 2

Figure 3.46 Lever analogy diagram of the first‐mode ECVT. (a) Stick diagram; (b) lever analogy diagram; (c) rescale the lever analogy diagram; (d) combined lever analogy diagram with gear‐shafts speed

Figure 3.47 Lever analogy diagram of the second‐mode ECVT. (a) Stick diagram; (b) lever analogy diagram; (c) rescale the lever analogy diagram; (d) combined lever analogy diagram with gear‐shaft speed

Figure 3.48 Free body diagram of a vehicle

Figure 3.49 The road load of the vehicle given in Example 3.8

Figure 3.50 Block diagram of a PID control algorithm

Chapter 04

Figure 4.1 The symbol (a), structure (b), and

i‐v

characteristics (c) of a diode

Figure 4.2 The symbol (a), structure (b), and

i‐v

characteristics (c) of a thyristor

Figure 4.3 The electrical circuit symbol and

pn

‐structure of a transistor. (a) PNP transistor, (b) NPN transistor

Figure 4.4 The steady‐state input and output characteristics of an

npn

transistor. (a) Common‐emitter circuit diagram, (b) Input characteristics, (c) Output (i‐v) characteristics

Figure 4.5 Circuit symbol and output characteristics of an

n‐

channel MOSFET. (a) The n‐channel MOSFET symbol and circuit diagram, (b) Output characteristics

Figure 4.6 Transfer characteristics of

n‐

channel depletion‐type and enhancement‐type MOSFETs. (a) The n-channel depletion‐type MOSFET, (b) The n‐channel enhancement‐type MOSFET

Figure 4.7 Steady‐state equivalent circuit of an

n‐

channel MOSFET

Figure 4.8 Switching‐mode equivalent circuit of an

n

‐channel MOSFET

Figure 4.9 Circuit symbol and equivalent circuit of an IGBT. (a) Circuit symbol of IGBT, (b) The equivalent circuit of IGBT

Figure 4.10 Typical transfer and

i‐v

characteristics of an IGBT. (a) Transfer characteristics, (b)

i‐v

characteristics

Figure 4.11 Basic principle circuit of a DC–DC converter. (a) Principle circuit diagram, (b) The switching control signal

Figure 4.12 PWM switch control diagram. (a) A PWM control diagram, (b) Periodic saw-tooth waveform and PWM control signal formation

Figure 4.13 Principle circuit for step‐down converters

Figure 4.14 Switch ON (a) and switch OFF (b) equivalent circuits of step‐down converters

Figure 4.15 Inductor current and voltage waveforms of the buck converter

Figure 4.16 Discontinuous‐conduction operational mode for buck converters

Figure 4.17 Output voltage ripple of buck converters

Figure 4.18 DC converter with a battery pack. (a) Schematic circuit, (b) Current waveform

Figure 4.19 Principle circuit of boost converters

Figure 4.20 Principle circuit of boost converters corresponding with the switch being (a) ON and (b) OFF

Figure 4.21 Inductor voltage and current on the continuous‐conduction mode of the boost converter

Figure 4.22 Capacitor charge and output voltage ripple of boost converters

Figure 4.23 Principle circuit of buck‐boost converters

Figure 4.24 Equivalent circuits for (a) switch ON and (b) switch OFF states in buck‐boost converters

Figure 4.25 Inductor voltage and current in the continuous‐conduction mode of a buck‐boost converter

Figure 4.26 Capacitor charge and output voltage ripple of buck‐boost converters

Figure 4.27 Principle circuit of a buck‐boost‐converter‐based PHEV battery charger

Figure 4.28 Principle circuit of a full‐bridge isolated buck converter

Figure 4.29 Main waveforms in steady‐state operation for a full‐bridge isolated buck converter

Figure 4.30 The principle circuit of a four‐quadrant DC–DC converter with a DC motor load. (a) Principle circuit, (b) The quadrant

Figure 4.31 Principle circuit of DC–AC inverters. (a) Principle circuit with resistive load, (b) Principle circuit with inductive load

Figure 4.32 Waveforms of the inverter principle circuit with resistive load

Figure 4.33 Waveforms of the inverter principle circuit with inductive load

Figure 4.34 Principle circuit and main waveforms of the single‐phase full‐bridge inverter. (a) Principle circuit of the single phase full bridge voltage source inverter, (b) The quadrant, (c) Main waveforms

Figure 4.35 Principle circuit of three‐phase bridge inverters

Figure 4.36 Voltage waveforms between the three terminals

Figure 4.37 Stator and rotor diagram of a BLDC motor. (a) The configuration of a rotor with 2 pairs of poles and 3 phase stator with 6 coils, (b) The electrical diagram of three phase stator

Figure 4.38 Magnetic field rotation (a) step 1; (b) step 2; (c) step 3; (d) step 4; (e) step 5; (f) step 6

Figure 4.39 Hall sensor signal, back emf, and output torque waveforms

Figure 4.40 Four‐quadrant operation of the electric motor in an HEV/EV

Figure 4.41 PID control diagram of a BLDC motor for HEV/EV applications

Figure 4.42 Torque–speed characteristics of BLDC motors for HEV/EV applications. (a) The principle torque‐speed characteristic curve, (b) The specified torque‐speed characteristic curve

Figure 4.43 Typical structure of a squirrel cage rotor for an AC induction motor

Figure 4.44 The equivalent circuit of an AC induction motor in steady‐state operation. (a) The equivalent circuit (b) The Thevenin equivalent circuit

Figure 4.45 Torque–speed characteristics of an AC induction motor. (a) Nature torque‐speed characteristics (b) The specified torque‐speed characteristics

Figure 4.46 Stationary frame three‐phase (

a

,

b

,

c

) to two‐phase orthogonal (

d

,

q

) axes transformation. (a) Stationary frame (a, b, c) to (d, q) axes transformation, (b) Three phase (a, b, c) axes, (c) Two phase orthogonal (d,q) axes

Figure 4.47 Stationary frame (

d

,

q

) to synchronous frame (

D

,

Q

) transformation

Figure 4.48 Block diagram of vector control for an AC induction motor in HEV/EV applications

Figure 4.49 General architecture of a PHEV/BEV battery charger

Figure 4.50 Voltage waveforms of a full‐bridge rectifier with a filter capacitor

Figure 4.51 The AC power triangle

Figure 4.52 Input voltage and current of the full‐bridge rectifier with filter capacitor

Figure 4.53 Operating principle of a PFC

Figure 4.54 Process required to charge a PHEV/BEV battery

Figure 4.55 PHEV/BEV charging control scheme

Chapter 05

Figure 5.1 Diagram of required ESS algorithms for HEV/PHEV/EV application

Figure 5.2 Diagram of current integration-based

SOC

estimation

Figure 5.3 Estimation error caused by sensor accuracy for the given current profile. (a) The calculated SOC; (b) the current profile

Figure 5.4 Estimation error caused by measuring power loss for the given current profile

Figure 5.5 Capacity vs. temperature for a Li‐ion battery cell

Figure 5.6 Coulombic charging efficiency vs. temperature for a Li‐ion battery cell

Figure 5.7 Example of a charge‐depleting current profile of a PHEV battery system

Figure 5.8 Calculated SOC based on the Coulomb counting method over the given current profile

Figure 5.9 Relationship between

V

oc

and the SOC of a Li‐ion battery cell

Figure 5.10 Electrical circuit equivalent model of a battery

Figure 5.11 Diagram of the voltage‐based SOC estimation method

Figure 5.12 The battery usage profiles. (a) The battery’s current (charge: +, discharge: −); (b) the battery’s terminal voltage; (c) the battery’s temperature

Figure 5.13 Estimated

V

oc

and SOC over the given profiles. (a) The estimated open‐circuit voltage of the battery pack; (b) the estimated battery SOC using the voltage‐based approach

Figure 5.14 Two RC pair electrical circuit equivalent model of a battery

Figure 5.15

V

oc

vs. SOC curve of an LiFePO

4

cell at 25 °C

Figure 5.16 Generalized electrical circuit equivalent model of a battery system

Figure 5.17 Relationship between a system’s transient response and pole location in the system

Figure 5.18 Voltage responses of an LiFePO4 battery cell to a 100 A step discharge current at 25 °C and different SOCs

Figure 5.19 Battery system model with fuzzy logic

Figure 5.20 Diagram of combined SOCs calculated using different approaches

Figure 5.21 The relationship between terminal voltage and terminal current. (a) Polarization of a battery under discharge current; (b) applied charge/discharge current at cell terminals; (c) voltage responses to the applied charge/discharge current

Figure 5.22 OCV–SOC relationship shifting over the calendar life of a Li‐ion battery at 35 °C and 80% SOC storage condition

Figure 5.23 OCV–SOC relationship shifting over 80% DoD cycle life of a Li‐ion battery at 35 °C

Figure 5.24 Maximal charge power availability of a Li‐ion cell at 25 °C

Figure 5.25 Maximal discharge power availability of a Li‐ion cell at 25 °C

Figure 5.26 Capacity fade with cycle number (80% DoD)

Figure 5.27 Internal resistance increase with storage time at 30 °C

Figure 5.28 Power evolution during storage at different temperatures and SOCs

Figure 5.29 Actual battery usage profile and the estimated battery resistance. (a) Actual battery usage profile (charge:

+

, discharge:

−

); (b) battery system terminal voltage; (c) battery system terminal current (charge: +, discharge: −); (d) the estimated battery system resistance

Figure 5.30 Life cycles vs. depth of discharge

Figure 5.31 Rainflow cycles corresponding to a given drive cycle. (a) The SOC swing diagram over a drive cycle; (b) the corresponding rainflow over the drive cycle

Figure 5.32 Comparsion of the discharge curves of a Li‐ion battery at C/20 at −40 °C.

Figure 5.33 Diagram of a current bypass cell‐balancing circuit

Figure 5.34 Diagram of capacitor‐based charge shuttle cell‐balancing circuit

Figure 5.35 Diagram of an inductive‐converter‐based cell‐balancing circuit

Figure 5.36 Natural balancing scenario with a lower capacity cell in the pack

Figure 5.37 Combined PI and feedforward cell‐balancing strategy

Figure 5.38 Cell‐balancing simulation model. (a) Battery system model with cell‐balancing algorithm; (b) individual cell model

Figure 5.39 The battery usage profile repeating the US06 drive schedule three times

Figure 5.40 Cell‐to‐cell parasitic load in a 32‐cell pack

Figure 5.41 Cell SOC variation at the start point of the evaluation period

Figure 5.42 Cell SOC variation after 15 weeks of vehicle operation with cell‐balancing hardware and algorithm active

Figure 5.43 Capacity variation of the battery pack

Figure 5.44 Cell SOC variation after 15 weeks of vehicle operation under the given conditions

Figure 5.45 Cell surface and core temperatures over an HEV driving cycle

Figure 5.46 Two‐parameter battery electrical circuit equivalent model

Figure 5.47 Cooling down or heating up process for battery temperature during the vehicle key‐off period

Figure 5.48 Example of a battery system efficiency test profile at 25 °C and 50% SOC

Chapter 06

Figure 6.1 Power split for a vehicle’s power demand based on a rule‐based energy strategy

Figure 6.2 Crisp set of vehicle speed

Figure 6.3 Fuzzy set of vehicle speed

Figure 6.4 Triangular fuzzy set expression

Figure 6.5 Trapezoidal fuzzy set expression

Figure 6.6 Fuzzy sets for HEV energy management

Figure 6.7 Fuzzy‐logic‐based HEV energy management strategy

Figure 6.8 Algorithmic diagram to find the optimal points for the ICE in an HEV

Figure 6.9 Golden section search

Figure 6.10 Process of optimizing operational points

Figure 6.11 Power versus speed (solid line) and torque versus speed (dashed line) curves of the ICE

Figure 6.12 Torque versus speed (solid line) and power versus speed (dashed line) curves of the generator

Figure 6.13 Torque versus speed (solid line) and power versus speed (dashed line) curves of the electric motor

Figure 6.14 Determined optimal operational points when the objective functions one and two are set as

and

Figure 6.15 Federal urban drive schedule of the USA

Figure 6.16 Required ICE power over the EPA75 drive cycle

Figure 6.17 Manually set operational points

Figure 6.18 Optimized operational point curve using

and

Figure 6.19 Fuel consumption comparison over an EPA drive cycle

Figure 6.20 NOx emissions comparison over an EPA drive cycle

Figure 6.21 CO emissions comparison over an EPA drive cycle

Figure 6.22 HC emissions comparison over an EPA drive cycle

Figure 6.23 The optimized operational points when

and

Figure 6.24 Fuel consumption comparison over an EPA drive cycle

Figure 6.25 NOx emissions comparison over an EPA drive cycle

Figure 6.26 CO emissions comparison over an EPA drive cycle

Figure 6.27 HC emissions comparison over an EPA drive cycle

Figure 6.28 A real‐time power split optimization algorithm

Figure 6.29 Optimal energy management strategy with a pattern recognition algorithm

Figure 6.30 Entire pattern recognition algorithm

Figure 6.31 Optimality principle

Chapter 07

Figure 7.1 The torque generation process for an SI engine

Figure 7.2 The torque generation process for a diesel engine

Figure 7.3 Schematic diagram of SI engine control

Figure 7.4 Schematic diagram of diesel engine control

Figure 7.5 Torque vacillation process

Figure 7.6 Concept of dumping engine torque fluctuation by the motor in an HEV

Figure 7.7 Diagram of electric motor dumping engine torque fluctuation

Figure 7.8 Sliding mode control and state trajectory

Figure 7.9 The sliding surface

Figure 7.10 The performance of sliding modes

Figure 7.11 High‐voltage bus and the connected loads

Figure 7.12 (a) Power and (b) voltage profiles on the high‐voltage bus of an HEV at −20 °C

Figure 7.13 Architecture of overvoltage protection control

Figure 7.14 Bang‐bang control signal turning ON/OFF setpoint

Figure 7.15 Diagram of overvoltage protection fuzzy logic control

Figure 7.16 Thermal control diagram for an HEV/EV battery system

Figure 7.17 Simplified thermal loop diagram

Figure 7.18 Combined PID and feedforward control diagram of battery thermal control

Figure 7.19 Optimal control

u

*

(

t

) and the change of state

T

*

ESS

(

t

) between the initial,

T

ESS

(0), and the final,

T

ESS

(

t

f

), set value

Figure 7.20 Adhesion/slip curves.

Figure 7.21 Traction motor torque control in a hybrid vehicle

Figure 7.22 HEV/EV anti‐rollback

Figure 7.23 Diagrams showing (a) passive, (b) semi‐active, and (c) active suspension systems

Figure 7.24 Diagrams of (a) rotary motor‐based and (b) linear motor‐based electric active suspension systems

Figure 7.25 Free body diagram of the suspension system of a quarter car

Figure 7.26 PID‐based active suspension control system

Figure 7.27 Exerted road disturbance

Figure 7.28 Vehicle body responses with/without PID‐based active suspension control

Figure 7.29 Tire/wheel responses with/without PID‐based active suspension control

Figure 7.30 Actuator output based on the PID control strategy

Figure 7.31 Actuator output electrical power based on the PID control strategy (+ power, − regen)

Figure 7.32 Model predictive‐based active suspension control system

Figure 7.33 Vehicle body responses with/without MPC‐based active suspension control

Figure 7.34 Tire/wheel responses with/without MPC‐based active suspension control

Figure 7.35 Actuator output based on the MPC control strategy

Figure 7.36 Actuator output electrical power based on the model predictive control strategy (+ power, − regen)

Figure 7.37 Vehicle speed and electrical energy consumption over repeated US06 cycles

Figure 7.38 Battery SOC and electrical power over repeated US06 cycles

Figure 7.39 Battery energy capacity decay scenarios over service years

Figure 7.40 Battery ten‐second discharge power capability degradation scenarios at 10% SOC at −30 °C

Figure 7.41

V

oc

vs. Ahr capacity characteristics of a Li‐ion battery

Figure 7.42 Two

RC

pair electrical circuit equivalent model of a battery

Figure 7.43 Adaptive recharge SOC termination setpoint control strategy

Figure 7.44 Example of battery SOC‐depleting window expansion over time

Figure 7.45 SOC‐depleting scenarios on repeated US06 cycles over time

Figure 7.46 Battery usable energy declining scenarios on repeated US06 cycles over time

Figure 7.47 Battery usable energy decay over time

Figure 7.48 The vehicle’s electric mileage loss over time

Figure 7.49 Battery charge‐sustaining example on repeated US06 cycles over time

Figure 7.50 An example of battery cold‐cranking capabilities over time at −20 °C

Figure 7.51 PI governing diagram of the algorithm for setting a PHEV battery lower SOC bound

Figure 7.52 SOC regulation process for the PI feedback control strategy

Figure 7.53 Battery power and vehicle speed curves from IVM to 80 mph acceleration

Figure 7.54 Battery kWh energy versus SOC curve around the CS‐operation zone

Figure 7.55 Example of a battery energy decay scenario

Figure 7.56 CS‐operation SOC setpoint online adaption strategy

Chapter 08

Figure 8.1 Current profile of a PHEV battery system when charged by an AC‐120 charger

Figure 8.2 Terminal voltage profile of a PHEV battery system when charged by an AC‐120 charger

Figure 8.3 SOC charging process of a PHEV battery system when charged by an AC‐120 charger

Figure 8.4 AC power‐charging profile

Figure 8.5 Current profile of a PHEV battery system charged by an AC‐240 charger

Figure 8.6 Terminal voltage profile of a PHEV battery system when charged by an AC‐240 charger

Figure 8.7 SOC charging process of a PHEV battery system when charged by an AC‐240 charger

Figure 8.8 AC power taken from an AC‐240 charger

Figure 8.9 Battery current profile at 3

C

‐rate fast charging

Figure 8.10 Battery terminal voltage profile during 3

C

‐rate fast charging at room temperature

Figure 8.11 Battery SOC changing curve at 3

C

‐rate fast charging

Figure 8.12 AC plug‐in charging control

Figure 8.13 OCV–SOC curve of an NMC‐based Li‐ion battery system at room temperature

Figure 8.14 PID plug‐in charging algorithm

Figure 8.15 Conversion from controller output to PWM duty signal

Figure 8.16 State‐space‐based DC fast‐charging control

Figure 8.17 Averaged five‐household daily load profiles in summer and winter

Figure 8.18 Averaged five‐household daily load plus charging of two PHEVs using an AC‐120 charger starting at 17:45 in summer and winter

Figure 8.19 Averaged five‐household daily load plus charging of two PHEVs using an AC‐120 charger starting at 00:00 in summer and winter

Figure 8.20 Averaged five‐household daily load plus charging of two PHEVs using an AC‐240 charger starting at 17:45 in summer and winter

Figure 8.21 Averaged five‐household daily load plus charging of two PHEVs using an AC‐240 charger starting at 00:00 in summer and winter

Figure 8.22 SOC usage vs. electric mileage for a PHEV

Figure 8.23 The actual operational SOC setpoint, end SOC point, and charge back SOC point

Figure 8.24 Optimal operational SOC setpoint, end SOC point, and charge back SOC point

Figure 8.25 The optimal plug‐in charge end point determination algorithm for PHEVs

Figure 8.26 Optimal plug‐in charging algorithm flow chart

Figure 8.27 Process of optimizing operational points using the dynamic programming method

Figure 8.28 Principle of the optimal decision made using the dynamic programming method

Chapter 09

Figure 9.1 Some typical sound pressure levels, SPLs (dB).

Figure 9.2 Some typical sound power levels,

L

w

(dB).

Figure 9.3 Frequency response of a one‐octave‐band filter

Figure 9.4 Simple free mass–spring vibration system. (a) Simple free mass‐spring system without damping, (b) Simple free mass‐spring system with damping

Figure 9.5 Viscous damped mass–spring vibration system. (a) An over-damped viscous‐damped motion, (b) A under‐damped viscous-damped motion

Figure 9.6 Simple viscous damped mass–spring system with harmonic excitation. (a) Simple viscous‐damped mass‐spring system with harmonic excitation, (b) Displacement amplitude of simple viscous‐damped mass-spring system with harmonic excitation

Figure 9.7 Simple source–path–receiver model

Figure 9.8 Driveline dynamics of hybrid electric vehicles

Figure 9.9 Engine speed, cranking torque, and floor vibration during a cold engine start at −25 °C

Figure 9.10 Gas exchange process of a four‐stroke ICE. (a) Intake stroke; (b) compression stroke; (c) power stroke; (d) exhaust stroke

Figure 9.11 Straight‐four engine configuration

Figure 9.12 Example of combustion pressure vs. ignition firing process

Figure 9.13 Piston stop position for engine start‐up vibration reduction

Figure 9.14 Cross‐section of the motor stator and rotor

Figure 9.15 Maxwell pressure distribution decomposition in sinusoidal force

Figure 9.16 Maxwell stress on the rotor

Figure 9.17 Static imbalance of the rotor

Figure 9.18 Couple imbalance of the rotor

Figure 9.19 Dynamic imbalance of the rotor

Figure 9.20 Periodic deformation of a magnetic core

Figure 9.21 Base operational frequency of switching mode power electronic devices

Figure 9.22 PI feedback with feedforward control strategy to adjust the switching frequency of power electronic devices

Figure 9.23 Switching frequency adjusted by a closed‐loop control strategy

Figure 9.24 Low‐frequency vibrations act on a vehicle chassis/body and battery pack

Figure 9.25 Driveline dynamics act on the battery pack

Figure 9.26 High‐voltage bus current of a battery‐powered electric vehicle during a repeated US06 drive cycle (positive: charge, negative: discharge)

Figure 9.27 High‐frequency voltage ripples superimposed on the high‐voltage bus of a PHEV

Figure 9.28 High‐frequency current ripples superimposed on the DC current of a PHEV

Chapter 10

Figure 10.1 Basic hybrid electric vehicle simulation system

Figure 10.2 FTP‐75 test schedule

Figure 10.3 EPA highway fuel economy test schedule

Figure 10.4 EPA urban dynamometer drive schedule

Figure 10.5 EPA HD‐UDDS drive schedule for heavy‐duty vehicles

Figure 10.6 NYCC drive schedule

Figure 10.7 SFTP‐US06 supplemental drive schedule

Figure 10.8 SC03 supplemental drive schedule

Figure 10.9 LA92 drive schedule

Figure 10.10 ECE test drive schedule

Figure 10.11 EUDC drive schedule

Figure 10.12 EUDC drive schedule for low‐power vehicles

Figure 10.13 NEDC drive schedule

Figure 10.14 WLTP drive schedule for Class 1 vehicles

Figure 10.15 WLTP drive schedule for Class 2 vehicles

Figure 10.16 WLTP drive schedule for Class 3 vehicles

Figure 10.17 Single cycle range and energy consumption test for battery‐powered vehicles

Figure 10.18 Multi‐cycle range test schedule

Figure 10.19 Multi‐cycle range test sequence

Figure 10.20 Engine speed vs. vehicle speed

Figure 10.21 Road load, traction limit, and 110 kW power line of the given vehicle

Figure 10.22 Torque–speed characteristics of the given engine

Figure 10.23 Traction capability of the given vehicle equipped with a one‐speed transmission

Figure 10.24 Traction capability of the given vehicle equipped with a two‐speed transmission

Figure 10.25 Traction capability of the given vehicle equipped with a three‐speed transmission

Figure 10.26 Traction capability of the given vehicle equipped with a four‐speed transmission

Figure 10.27 Diagram of arithmetic progression

Figure 10.28 Diagram of geometric progression

Figure 10.29 Diagram of harmonic progression

Figure 10.30 Wide‐open‐throttle torque and power for the engine of Example 10.1

Figure 10.31 Road load power of the given vehicle

Figure 10.32 Road load power and wheel power in first and top gears of the given vehicle

Figure 10.33 Overall road load power and wheel power at the preliminary gear ratios for the given vehicle

Figure 10.34 Driveshaft speed, torque, and power during FTP city drive schedule

Figure 10.35 Driveshaft speed, torque, and power during FTP highway drive schedule

Figure 10.36 Driveshaft torque and power vs. speed during FTP city drive schedule

Figure 10.37 Driveshaft torque and power vs. speed during FTP highway drive schedule

Figure 10.38 Characteristics of the initially selected electric motor set

Figure 10.39 Wheel and road power of the vehicle described in Example 10.2

Figure 10.40 Examples of UDDS energy consumption test layouts for CD modes of PHEVs

Figure 10.41 Examples of HWFET energy consumption test layouts for CD modes of PHEVs

Figure 10.42 Transition cycle, Rcdc, and Rcda definitions in energy consumption tests for PHEVs

Figure 10.43 End‐of‐test scenarios in energy consumption tests for PHEVs

Figure 10.44 Example of a window sticker for an electric vehicle (EPA, 2011)

Figure 10.45 Example of a window sticker for a plug‐in hybrid electric vehicle (EPA, 2011)

Figure 10.46 FTP UDDS drive schedule

Figure 10.47 SOC depletion of the first phase UDDS run

Figure 10.48 Battery usage of the first phase UDDS run

Figure 10.49 DC electrical energy consumption of the first phase UDDS run

Figure 10.50 SOC depletion of the last three phases of UDDS running

Figure 10.51 Battery usage of the last three phases of UDDS running

Figure 10.52 DC electrical energy consumption of the last three phases of UDDS running

Figure 10.53 HWFET drive schedule

Figure 10.54 SOC depletion of the first phase HWFET run

Figure 10.55 Battery usage of the first phase HWFET run

Figure 10.56 DC electrical energy consumption of the first phase HWFET run

Figure 10.57 SOC depletion of the last three phases of HWFET running

Figure 10.58 Battery usage of the last three phases of HWFET running

Figure 10.59 DC electrical energy consumption of the last three phases of HWFET running

Appendix A

Figure A.1 System with input and output

Figure A.2 System with disturbance

Figure A.3 Examples of noise signals

Figure A.4 Continuous and sampled data functions

Figure A.5 Input and output of sampler and holder

Appendix B

Figure B.1 Open‐loop control system diagram

Figure B.2 Closed‐loop control system diagram

Figure B.3 Working diagram of the dynamic programming method

Figure B.4 Diagram of the optimal LQC feedback control system

Figure B.5 Obtained optimal feedback control system

Figure B.6 Minimal variance control system diagram

Figure B.7 Diagram of self‐tuning control system

Figure B.8 Diagram of model reference adaptive control system

Figure B.9 Implemented adaptive control system diagram based on the MIT rule

Figure B.10 Scheme of model predictive control

Figure B.11 Diagram of a hardware redundant control system

Figure B.12 Diagram of a software redundant control system

Guide

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Automotive Series

Series Editor: Thomas Kurfess

Automotive Aerodynamics

Katz

April 2016

The Global Automotive Industry

Nieuwenhuis and Wells

September 2015

Vehicle Dynamics

Meywerk

May 2015

Vehicle Gearbox Noise and Vibration: Measurement, Signal Analysis, Signal Processing and Noise Reduction Measures

Tůma

April 2014

Modeling and Control of Engines and Drivelines

Eriksson and Nielsen

April 2014

Modelling, Simulation and Control of Two‐Wheeled Vehicles

Tanelli, Corno and Savaresi

March 2014

Advanced Composite Materials for Automotive Applications: Structural Integrity and Crashworthiness

Elmarakbi

December 2013

Guide to Load Analysis for Durability in Vehicle Engineering

Johannesson

November 2013

HYBRID ELECTRIC VEHICLE SYSTEM MODELING AND CONTROL

Second Edition

Wei Liu

General Motors, USA

This edition first published 2017© 2017 John Wiley & Sons Ltd

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

The right of Wei Liu to be identified as the author of this work has been asserted in accordance with law.

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Library of Congress Cataloging‐in‐Publication Data

Names: Liu, Wei, 1960 August 30- author.Title: Hybrid electric vehicle system modeling and control / Wei Liu.Other titles: Introduction to hybrid vehicle system modeling and controlDescription: 2nd edition. | Chichester, West Sussex, UK ; Hoboken, NJ, USA : John Wiley & Sons, Inc., 2017. | Series: Automotive series | Revised edition of: Introduction to hybrid vehicle system modeling and control. | Includes bibliographical references and index.Identifiers: LCCN 2016045440 (print) | LCCN 2016048636 (ebook) | ISBN 9781119279327 (cloth) | ISBN 9781119279334 (pdf) | ISBN 9781119278948 (epub)Subjects: LCSH: Hybrid electric vehicles--Simulation methods. | Hybrid electric vehicles--Mathematical models.Classification: LCC TL221.15 .L58 2017 (print) | LCC TL221.15 (ebook) | DDC 629.22/93--dc23LC record available at https://lccn.loc.gov/2016045440

Cover design by WileyCover image: Martin Pickard/ Henrik5000/ dreamnikon/ Gettyimages

To my wife Mei and son Oliver

Preface

With hybrid electric vehicle systems having undergone many great changes in recent years, hybrid electric vehicle modeling and control techniques have also advanced. Electrified powertrains are providing dramatic new opportunities in the automotive industry. Since hybrid vehicle systems naturally have nonlinear characteristics, exhibit fast parameter variation, and operate under uncertain and changing conditions, the associated modeling and control problems are extremely complex. Nowadays, hybrid vehicle system engineers must face head‐on the challenge of mastering cutting‐edge system modeling and control theories and methodologies in order to achieve unprecedented vehicle performance.

Hybrid electric vehicle systems, combining an internal combustion engine with one or more electric motors for propulsion, operate in changing environments involving different fuels, load levels, and weather conditions. They often have conflicting requirements and design objectives that are very difficult to formalize. Most hybrid controls are fundamentally multivariable problems with many actuators, performance variables, and sensors, but some key control variables are not directly measurable. To articulate these challenges, I published the first edition of this book in 2013 to meet the needs of those involved in hybrid vehicle system modeling and control development.

Continued advances in hybrid vehicle system technology make periodic revision of technical books in this area necessary in order to meet the ever‐increasing demand for engineers to look for rigorous methods for hybrid vehicle system control design and analysis. The principal aims of this revision are to place added emphasis on advanced control techniques and to expand the various modeling and analysis topics to reflect recent advances in hybrid electric vehicle systems. Overall, many parts of the book have been revised. The most apparent change is that a chapter on noise and vibration has been added to present the unique control challenges arising in hybrid electric vehicle integration to meet driving comfort requirements.

The material assembled in this book is an outgrowth of my over fifteen years’ work on hybrid vehicle research, development, and production at the National Research Council Canada, Azure Dynamics, and General Motors. The book is intended to contribute to a better understanding of hybrid electric vehicle systems, and to present all the major aspects of hybrid vehicle modeling, control, simulation, performance analysis, and preliminary design in the same book.

This revised edition retains the best of the first edition while rewriting some key sections. The basic structure of the book is unchanged. The book consists of ten main chapters and two appendices. Chapter 1 provides an introduction to hybrid vehicle system architecture, energy flow, and the controls of a hybrid vehicle system. Chapter 2 reviews the main components of a hybrid system and their characteristics, including the internal combustion engine, the electric motor/generator, the energy storage system, and hybrid electric transmission. This chapter also introduces the construction, basic materials, and requirements of Li‐ion batteries for hybrid electric vehicle application.

Chapter 3 presents detailed mathematical models of hybrid system components for system design and simulation analysis, which include the internal combustion engine, the transmission system, the motor/generator, the battery system, and the vehicle body system, as well as the driver. One‐mode and two‐mode electrical continuously variable transmission system modeling and the lever analogy technique are introduced for hybrid transmission kinematic analysis in this chapter. The models presented in this chapter can be used either for individual component analysis or for building a whole vehicle simulation system.

Chapter 4 introduces the basics of power electronics and electric motor drives applied in hybrid electric vehicle systems. The characteristics of commonly used power electronic switches are presented first, followed by the introduction of the operational principles of the DC–DC converter and DC–AC inverter. Brushless DC motors and AC induction motors and their control principles are also introduced for hybrid vehicle applications. The techniques of plug‐in charger design are presented in the last part of this chapter.

Chapter 5 addresses the modeling and controls of the energy storage system. Algorithms relating to the battery system play a very important role in hybrid electric vehicle systems because they directly affect the overall fuel economy and drivability and safety of a vehicle; however, due to the complexity of electrochemical reactions and dynamics as well as the availability of key variable measurements, hybrid vehicle system and algorithm engineers are facing head‐on technical challenges in the development of the algorithms required for hybrid electric vehicles. In this chapter, the state of charge determination algorithms and technical challenges are first discussed. Then, the power capability algorithms and state of life algorithms with aging behavior and the aging mechanism are addressed, and the lithium metal plating issue and symptoms in Li‐ion batteries are discussed as well. The cell‐balancing algorithm necessary for hybrid vehicles, the battery cell core temperature estimation method, and the battery system efficiency calculation are also presented in this chapter.

Chapter 6 is concerned with the solution of energy management problems under different drive cycles. Both direct and indirect optimization methods are discussed. The methods presented in this chapter can be treated as the most general and practical techniques for the solution of hybrid vehicle energy management problems.

Chapter 7 elaborates on the other control problems in hybrid vehicle systems, including active engine fluctuation torque dumping control, voltage ripple control in the high‐voltage bus, thermal control of the energy storage system, motor traction and anti‐rollback control, and electric active suspension system control. For plug‐in hybrid vehicles, the CS setpoint self‐tuning control strategy and the CS lower bound real‐time determination algorithm are presented to compensate for battery aging in this chapter.

Chapter 8 discusses the characteristics of AC‐120, AC‐240, and fast public plug‐in charging for emerging plug‐in hybrid and purely battery‐powered vehicles. This chapter also presents plug‐in charge control requirements and techniques for battery‐powered electric vehicles. The impact of plug‐in charging on battery life and safety as well as on the electric grid and power distribution system is presented in this chapter. In addition, the various plug‐in charging strategies, including the optimal charging strategy, are introduced in this chapter.

Chapter 9 deals with noise and vibration issues. Noise and vibration have become an important aspect of hybrid powertrain development and the vehicle integration process, and there are stringent requirements to reduce HEV/PHEV/BEV vibration and noise levels. To articulate these challenges, this chapter first introduces the basics of vibration and noise, and then addresses the unique vibration and noise characteristics and issues associated with powertrain vibration, driveline vibration, gear rattle noise, and electrified‐component‐specific vibration and noise, such as accessory whine, motor/generator electromagnetic vibration and noise, and vibration and growl in the energy storage system, as well as vibration and noise pattern changes compared with traditional vehicles.

Chapter 10 presents typical cycles and procedures for fuel economy, emissions, and electric range tests, including FTP, US06, SC03, LA92, NEDC, and WLTP for hybrid electric vehicles, as well as single and multiple cycles for battery‐powered electric vehicles. The necessary calculations and simulations for sizing/optimizing components and analyzing system performance at the concept/predesign stage of a hybrid vehicle system are addressed in this chapter.

Appendix A reviews the system identification, state and parameter estimation methods and techniques. Commonly used mathematical models are introduced for hybrid vehicle system control algorithm development. Recursive least squares and generalized least squares techniques are presented for parameter estimation. The Kalman filter and extended Kalman filter are introduced in this appendix to solve state and parameter estimation problems. In addition, the appendix also presents the necessary computational stability enhancement techniques of practical hybrid vehicle systems.

Appendix B briefly introduces some advanced control methods which are necessary to improve the performance of a hybrid electric vehicle system. These include system pole‐placement control, objective‐function‐based optimal control, dynamic‐programming‐based optimal control, minimal variance, and adaptive control techniques for systems with stochastic behavior. To enhance the reliability and safety of a hybrid vehicle system, fault‐tolerant control strategies are briefly introduced in this appendix.

In the hybrid electric vehicle system control field, there are many good practices that cannot be fully justified from basic principles. These practices are the ‘art’ of hybrid vehicle system control, and thus several questions arise for control engineers and researchers on the future control of hybrid vehicle systems: What form will scientific underpinnings take to allow control engineers to manage and control vehicle systems of unprecedented complexity? Is it time to design real‐time control algorithms that address dynamic system performance in a substantial way? Is it feasible to develop a control methodology depending on ideas originating in other scientific traditions in addition to the dependence on mathematics and physics? Such questions provide strong evidence that control has a significant role to play in hybrid electric vehicle engineering.

This book has been written primarily as an engineering reference book to provide a text giving adequate coverage to meet the ever‐increasing demand for engineers to look for rigorous methods for hybrid electric vehicle design and analysis. It should enable modeling, control, and system simulation engineers to understand the hybrid electric vehicle systems relevant to control algorithm design. It is hoped that the book’s conciseness and the provision of selected examples illustrating the methods of modeling, control, and simulation will achieve this aim. The book is also suitable for a training course on hybrid electric vehicle system development with other supplemental materials. It can be used both on undergraduate and graduate‐level hybrid vehicle modeling and control courses. I hope that my efforts here succeed in helping you to understand better this most interesting and encouraging technology.