Control strategies of permanent magnet synchronous motor drive for electric vehicles

List of Figures Figure 3.2 Representation of a simplified permanent magnet synchronous motor PMSM drive with speed and current controller.. ...57 Figure 3.11 Torque response of the s

CONTROL STRATEGIES OF PERMANENT MAGNET

SYNCHRONOUS MOTOR DRIVE FOR ELECTRIC

VEHICLES

Chiranjit Sain, Atanu Banerjee

and Pabitra Kumar Biswas

Control Strategies of Permanent Magnet

Synchronous Motor Drive for Electric Vehicles

Control Theory and Applications

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1 Control Strategies of Permanent Magnet Synchronous Motor

Drive for Electric Vehicles

Chiranjit Sain, Atanu Banerjee and Pabitra Kumar Biswas

Control Strategies of Permanent Magnet

Synchronous Motor Drive for Electric Vehicles

Chiranjit Sain Atanu Banerjee Pabitra Kumar Biswas

MATLAB® and Simulink® are trademarks of The MathWorks, Inc and are used with permission The MathWorks does not warrant the accuracy of the text or exercises in this book This book’s use or discussion of MATLAB® and Simulink® software or related products does not constitute endorsement or sponsorship by The MathWorks of a particular pedagogical approach or particular use of the MATLAB® and Simulink® software.

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© 2023 Chiranjit Sain, Atanu Banerjee and Pabitra Kumar Biswas

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Contents

List of Figures xi

List of Tables xix

Preface xxi

Acknowledgements xxiii

Authors xxv

List of Symbols xxvii

Chapter 1 Introduction 1

1.1 Background and Problem Formulation 1

1.2 Review of Mathematical Modelling and Open- Loop-Based Control Strategy of a Self-Controlled PMSM Drive 2

1.2.1 Literature Survey 2

1.3 Review of Closed- Loop-Based Control Strategy of a PMSM Drive 3

1.3.1 Literature Survey 4

1.3.2 Review of Fuzzy Logic-Controlled PWM-Operated PMSM Drive 4

1.4 Development of Different Control Strategies of a PMSM Drive 5

1.4.1 Literature Survey 6

1.5 Solar-Powered PMSM Drive Smart Electric Vehicle for Sustainable Development 7

1.5.1 Literature Survey 8

1.6 Smart Technology-Based Solar-Powered Electric Vehicle 9

1.7 Industrial Linkage in Smart Electric Vehicles 12

1.8 Research Objectives 13

1.9 Outline of the Thesis 14

Chapter 2 Mathematical Modelling and Dynamic Performance Evaluation of a Self-Controlled Permanent Magnet Synchronous Motor Drive 17

2.1 Introduction 17

2.2 Contribution 18

2.3 Development of Mathematical Modelling and System Description 19

2.3.1 Modelling of PWM-Operated Three-Phase Voltage Source Inverter Topology 20

2.3.2 Transformation of abc-dq0 Matrix in Rotor Reference Frame 21

2.3.3 Modelling of PMSM Machine 22

2.4 Concept of Sensor Angle and Rotor Position Estimation 25

viii Contents

2.5 Simulation Results and Discussion 272.5.1 Performance Indices of a PMSM Drive without Sensor Angle Optimization 292.5.2 Comparative Performance Analysis with Sensor Angle-Based Optimization ( No-Load Operation) 302.5.3 Comparative Performance Analysis with Sensor Angle-Based Optimization ( On-Load Operation) 332.5.4 Some Case Studies under Various Operating

Conditions 372.5.5 Illustration of Dynamic Behaviour of a PMSM

Drive at Various DC Link Voltages 392.5.6 Illustration of Dynamic Behaviour of a PMSM

Drive at Various Load Torques 412.6 Experimental Results and Discussions 412.7 Chapter Summary 48

Chapter 3 Design and Comparative Analysis of Closed-Loop Control

Strategy in a Simplified PMSM Drive Using Various Classical and Fuzzy Logic Controllers 493.1 Introduction 493.2 Contribution 503.3 Establishment of Mathematical Model of a Simplified

Closed-Loop PMSM Drive 513.4 Performance Evaluation of a Simplified PMSM Drive

Using Proportional Integral Controller 553.5 Performance Evaluation of Proposed Simplified Closed-Loop PMSM Drive Using Lead Speed Compensator 563.6 Performance Evaluation of Proposed Simplified Closed-Loop PMSM Drive Using Lead-Lag Speed Compensator 603.7 Investigation of a Closed-Loop PMSM Drive Employing PID Controller 613.8 Discussion and Comparative Performance Evaluation

between a PI- and PID-Controlled Simplified PMSM Drive 633.9 Observation of Various Case Studies 703.10 Development of Fuzzy Logic Controller for Simplified

Closed-Loop Model of a Simplified PMSM Drive 733.10.1 Development of Fuzzy Logic Controller Rule Base 753.10.2 Dynamic Performance Evaluation of Fuzzy

Logic Speed-Controlled PMSM Drive 753.10.3 Performance Indices of Control System Use

Different Controllers ( Time Domain and Frequency Domain) 773.10.4 Optimization of Dynamic Performance of

Fuzzy-Controlled PMSM Drive 783.11 Chapter Summary 79

Contents

Chapter 4 Illustration of a Fuzzy-Controlled PWM-Operated PMSM Drive

Employed in Light Electric Vehicle 81

4.1 Introduction 81

4.2 Contribution 82

4.3 Proposed System Description 83

4.3.1 Design Considerations of a Fuzzy Speed Controller 88

4.4 Performance of a Light Electric Vehicle 91

4.5 Simulation Results and Discussion 92

4.6 Experimental Results and Discussion 100

4.7 Chapter Summary 106

Chapter 5 Development of Control Strategy of a Vector-Controlled PMSM Torque Drive for Energy-Efficient Electric Vehicle 109

5.1 Introduction 109

5.2 Contribution 111

5.3 Mathematical Modelling and Proposed System Description 111

5.3.1 Analysis of a Hysteresis Current Controller 116

5.3.2 Modelling of an Energy-Efficient Electric Vehicle 117

5.4 Simulation Results and Discussion 118

5.4.1 Performance of an Energy-Efficient Electric Vehicle 122

5.4.2 Some Case Studies 125

5.5 Experimental Investigation 130

5.6 Chapter Summary 134

Chapter 6 Conclusions and Future Work 135

6.1 Conclusions 135

6.2 Future Work 136

References and Further Reading 137

Index 147

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List of Figures

Figure 1.1 Layout representation of a solar-powered smart electric vehicle 10

Figure 1.2 Smart technology-based charging solution for a

modern electric vehicle 10

Figure 1.3 Image of a solar-powered smart electric vehicle 11

Figure 1.4 Internet of Things ( IoT)-based architecture for

a smart electric vehicle 11

Figure 2.1 System layout representation of the proposed PMSM drive .20

Figure 2.2 Representation of permanent magnet synchronous motor .23

Figure 2.3 Representation of a simplified ( a) d-axis equivalent circuit and

( b) q-axis equivalent circuit of a PMSM machine .24

Figure 2.4 Geometrical representation of the space vector topology while

( a) sensor angle ( sang) = 0° and ( b) sensor angle ( sang) = −30° .26

Figure 2.5 Orientation of the field mmf ( Mf) and the armature voltage

( Va) space vectors at different switching instants ( a) while 6,

1 and 2 are ON and rotor position θr= −30° and ( b) when rotor position θr= +30°, ( c) while 1, 2 and 3 are ON and rotor position

θr= 30°, ( d) when 2, 3 and 4 are ON and rotor position θr= 90°, ( e) while 3, 4 and 5 are ON and rotor position θr= 150° and

( f) when 4, 5 and 6 are ON and rotor position θr= 210° .27

Figure 2.6 Flowchart for the dynamic simulation of proposed algorithm 29

Figure 2.7 Variation of ( a) speed vs time, ( b) torque vs time, ( c) phase

voltage, ( d) phase current, ( e) quadrature axis current and

( f) rotor position estimation response .30

Figure 2.8 Response of ( a,b) speed, ( c,d) electromagnetic torque, ( e,f)

q-axis current, ( g,h) phase voltage, ( i,j) phase current and ( k,l) rotor position estimation vs time response while Tl= 0 Nm

applied and due to the variation in sensor lead angle 31

Figure 2.9 Comparative analysis of ( a,b) speed, ( c,d) electromagnetic

torque, ( e,f) q-axis current, ( g,h) phase voltage, ( i,j) phase

current and ( k,l) rotor position estimation vs time response

while Tl= 7 Nm is applied and due to the variation in sensor

lead angle .34

xii List of Figures

Figure 2.10 Comparative dynamic analysis of ( a,b) d-axis current,

( c,d)  torque-speed curve, ( e,f) d-axis voltage and ( g,h)

q-axis voltage due to the variation in sensor angle in a

PMSM machine .36

Figure 2.11 Phase voltage waveform when 96 V is employed at the dc link in ( a) transient condition and ( b) steady-state condition 37

Figure 2.12 Electromagnetic torque vs time waveform with operating conditions same in ( a) transient condition and ( b) steady-state condition 37

Figure 2.13 Phase current waveform in ( a) transient condition and ( b)  steady-state condition 38

Figure 2.14 Variation of ( a) speed, ( b) rotor position, ( c) phase voltage and ( d) torque-speed curve due to the change in mechanical parameters 39

Figure 2.15 Response of speed, torque, phase voltage, phase current and rotor position response when 48 V and 96 V are applied with Tl= 0 .40

Figure 2.16 Response of (a) speed, (b) torque, (c) phase current and (d) phase voltage vs time response with Tl= 5 Nm applied .42

Figure 2.17 Image of the experimental test rig 43

Figure 2.18 Layout diagram of the proposed hardware circuitry .44

Figure 2.19 Real-time response of ( a) inductor current in a buck-type VSI and gate pulses of the power switches, ( b) line voltage of the inverter, ( c) phase voltages of the inverter and ( d) generated emf and armature current on no-load and on-load operation of a PMSM machine 45

Figure 2.20 Real-time variation of ( 1) phase A current under transient condition, ( 2) phase B current under transient condition, ( 3) armature current at steady-state condition and ( 4) inverter output current 46

Figure 2.21 Variation of speed at various samples taken in the real-time set-up .46

Figure 2.22 Measurement of speed at various samples with load variations 47

Figure 2.23 Rotor position vs time response in real-time set-up 47

Figure 2.24 Experimental analysis of the torque-speed curve 47

Figure 3.1 Schematic representation of the proposed permanent magnet synchronous motor ( PMSM) drive .50

List of Figures

Figure 3.2 Representation of a simplified permanent magnet synchronous

motor ( PMSM) drive with speed and current controller 51

Figure 3.3 Block diagram of the proposed simplified permanent magnet

synchronous motor ( PMSM) drive 52

Figure 3.4 Current control loop 53 Figure 3.5 Simplified speed control loop 53 Figure 3.6 Simplified block diagram representation of a conventional

proportional integral ( PI) controller 55

Figure 3.7 Time domain characteristics of two-loop current structure

both using proportional integral ( PI) controller 56

Figure 3.8 Bode plot response of two-loop control structure .56 Figure 3.9 Root locus response of two-loop control structure 57 Figure 3.10 Speed variation of the simplified permanent magnet

synchronous motor ( PMSM) drive: ( a) no-load operation,

Tl= 0 and ( b) on-load operation, Tl= 5 Nm .57

Figure 3.11 Torque response of the simplified permanent magnet

synchronous motor ( PMSM) drive: ( a) no-load operation,

Tl= 0 and ( b) on-load operation, Tl= 5 Nm .57

Figure 3.12 Bode plot response of two-loop control structure 58 Figure 3.13 Root locus response of two-loop control structure 58 Figure 3.14 Speed variation of the simplified permanent magnet

synchronous motor ( PMSM) drive: ( a) no-load operation,

Tl= 0 and ( b) on-load operation, Tl= 5 Nm .59

Figure 3.15 Torque response of the simplified permanent magnet

synchronous motor ( PMSM) drive: ( a) no-load operation,

Tl= 0 and ( b) on-load operation, Tl= 5 Nm .59

Figure 3.16 Bode plot response of the proposed two-loop control structure .60 Figure 3.17 Root locus response of two-loop control structure 61 Figure 3.18 Speed response of the simplified permanent magnet

synchronous motor ( PMSM) drive: ( a) no-load operation,

Tl= 0 and ( b) on-load operation, Tl= 5 Nm .62

Figure 3.19 Torque profile of the proposed simplified permanent magnet

synchronous motor ( PMSM) drive: ( a) no-load operation,

Tl= 0 and ( b) on-load operation, Tl= 5 Nm .62

xiv List of Figures

Figure 3.20 MATLAB/Simulink model of a closed-loop permanent

magnet synchronous motor ( PMSM) drive using P current

controller and proportional integral derivative ( PID) speed

controller .64

Figure 3.21 Step response characteristics of the exact current loop .65 Figure 3.22 Step response curve of simplified speed control loop with a

proportional integral ( PI) controller .65

Figure 3.23 Step response of simplified speed loop with a proportional

integral derivative ( PID) controller 66

Figure 3.24 Comparative step response behaviour of overall control loop

using proportional integral derivative ( PID) and proportional integral ( PI) controller .66

Figure 3.25 Comparative bode diagram analysis of overall control loop

using proportional integral derivative ( PID) and proportional

integral ( PI) controller 67

Figure 3.26 Comparative root locus plot analysis of overall control

loop using a proportional integral derivative ( PID) and

proportional integral ( PI) controller 67

Figure 3.27 Dynamic response of speed using a P current controller and a

proportional integral ( PI) speed controller when a step change

in reference speed of 20 rad/ s is introduced 68

Figure 3.28 Dynamic response of torque using a P current controller and a

proportional integral ( PI) speed controller 68

Figure 3.29 Dynamic response of speed waveform using current and speed

both proportional integral ( PI) controller .68

Figure 3.30 Dynamic response of torque of the closed-loop drive using

current and speed both proportional integral ( PI) controller .69

Figure 3.31 Speed response using a P current controller and a proportional

integral derivative ( PID) speed controller .69

Figure 3.32 Dynamic response of torque of the permanent magnet

synchronous motor ( PMSM) drive using a P current controller and a proportional integral derivative ( PID) speed controller 70

Figure 3.33 Step response of overall speed and current loop using

proportional integral ( PI) and proportional integral

derivative ( PID) controller 70

Figure 3.34 Bode diagram curve of overall speed and current loop

using proportional integral ( PI) and proportional integral

derivative ( PID) controller 71

List of Figures

Figure 3.35 Root locus plot of overall speed and current loop using

proportional integral ( PI) and proportional integral

derivative ( PID) controller 71

Figure 3.36 Step response characteristics of overall speed and current loop

both using proportional integral derivative ( PID) controller 72

Figure 3.37 Bode diagram curve of overall speed and current loop both

using proportional integral derivative ( PID) controller 72

Figure 3.38 Root locus plot representation of overall speed and

current loop both using proportional integral derivative ( PID) controller 73

Figure 3.39 Structure of a fuzzy interface system 74 Figure 3.40 Membership function plot for the input variable 74 Figure 3.41 Representation of MF of the second input function ‘ change in

speed error’ 75

Figure 3.42 Membership function of output variable q-axis current 75 Figure 3.43 Representation of fuzzy logic surface viewer 76 Figure 3.44 Speed variation of the simplified permanent magnet

synchronous motor ( PMSM) drive using fuzzy speed

controller: ( a) no-load operation, Tl= 0 and ( b) on-load

operation, Tl= 5 Nm .76

Figure 3.45 Torque profile of the proposed simplified permanent magnet

synchronous motor ( PMSM) drive using fuzzy speed

controller ( a) no-load operation, Tl= 0 and ( b) on-load

operation, Tl= 5 Nm .77

Figure 3.46 ( a) Comparative time domain analysis of overall speed and

current loop using proportional integral ( PI), lead and

lead-lag controller, ( b) reference tracking after tuning effort,

( c) performance optimization of controller, ( d) bode diagram

of reference tracking after tuning, ( e) steady-state step

response of permanent magnet synchronous motor ( PMSM)

drive after tuning and ( f) steady-state bode diagram of drive system after tuning 78

Figure 4.1 Block diagram representation of the overall permanent

magnet synchronous motor ( PMSM) drive system 83

Figure 4.2 ( a) Detailed structure layout for the development of various

sub-systems ( b) Detailed MATLAB/Simulink model of the

‘ sinusoidal pulse width modulation ( SPWM) block’ of ( a)

( c) Detailed Simulink model of ‘ the inverter block’ of ( a) .84

xvi List of Figures

Figure 4.3 Structure of a fuzzy interface system .89 Figure 4.4 Representation of membership function for proposed input

variables: ( a) speed error and ( b) change in speed error 89

Figure 4.5 Membership function plot of output variable q-axis current .90 Figure 4.6 ( a) Fuzzy logic surface viewer for different fuzzy rules

( b) Formation of adaptive fuzzy logic rule viewer .90

Figure 4.7 Detailed MATLAB/Simulink-based closed-loop model of

a permanent magnet synchronous motor ( PMSM) drive .92

Figure 4.8 Generation of pulse width modulation ( PWM) signals applied

to permanent magnet synchronous motor ( PMSM) 93

Figure 4.9 Sinusoidal pulse width modulation ( SPWM) pulses after

implementing switching logic .94

Figure 4.10 Fast Fourier transform ( FFT) analysis of ( a) voltage and

( b) current based on percentage of fundamental for VSI .95

Figure 4.11 Fast Fourier transform ( FFT) analysis of ( a) voltage and

( b) current based on percentage of fundamental for buck

converter-fed VSI .96

Figure 4.12 ( a) Simulated phase voltage vs time waveform as predicted

by the detailed Simulink-based closed-loop adjustable speed

permanent magnet synchronous motor ( PMSM) ( b) Simulated d-axis stator voltage ( Vds) vs time waveform .97

Figure 4.13 Bode plot response of the proposed control structure .97 Figure 4.14 ( a) Dynamic response of speed and ( b) electromagnetic

torque response .98

Figure 4.15 ( a) Electromagnetic torque vs time response when load torque

Tl= 10 Nm is applied and ( b) q-axis current vs time response

as predicted by the Simulink model .98

Figure 4.16 ( a) Typical process flow diagram for electric scooter

simulation, ( b) approximate distance travelled curve for

the design of an electric scooter and ( c) typical acceleration

response for the design of an electric scooter .99

Figure 4.17 Circuit diagram of the proposed hardware circuitry 101 Figure 4.18 ( a) Image of the prototype inverter circuitry and

(b) experimental test bench 102

Figure 4.19 Captured real-time pulse width modulation ( PWM) pulses

from six MOSFET switches: ( a) MOSFET-1, ( b) MOSFET-2, ( c) MOSFET-3, ( d) MOSFET-4, ( e) MOSFET-5 and

( f)  MOSFET-6 102

List of Figures

Figure 4.20 ( a) Real-time captured armature current of permanent magnet

synchronous motor ( PMSM) machine and ( b) real-time

captured d-axis voltage response 103

Figure 4.21 Real-time armature phase voltage 103

Figure 4.22 Real-time speed variation of the permanent magnet synchronous motor ( PMSM) motor 104

Figure 4.23 Speed estimation using real and proposed method 105

Figure 4.24 Fast Fourier transforms of the ( a) voltage and ( b) current waveforms based on amplitude on hardware for VSI 105

Figure 4.25 Fast Fourier transforms of the ( a) voltage and ( b) current waveforms based on amplitude on hardware for proposed buck  converter-fed VSI 106

Figure 4.26 Real-time response of dc link current ( a) on no-load operation and ( b) on-load operation 106

Figure 5.1 Schematic diagram of the proposed PMSM drive system 112

Figure 5.2 Phasor diagram of a surface-mounted PMSM machine 114

Figure 5.3 Proposed power circuit representation of the inverter 116

Figure 5.4 Representation of a hysteresis current controller 117

Figure 5.5 ( a) Simplified MATLAB simulation model of the proposed torque-controlled PMSM drive ( b) Process flow diagram for the dynamic simulation of the proposed algorithm 119

Figure 5.6 Comparative dynamic analysis of ( a,b) torque, ( c,d) speed, ( e,f) torque angle, ( g,h) q-axis current, ( i,j) three-phase stator current, ( k,l) steady-state armature current, ( m,n) flux linkage and ( o,p) d-axis current using a hysteresis current controller and a PWM current controller of a torque-controlled permanent magnet synchronous motor drive with identical operating conditions 121

Figure 5.7 Typical process flow diagram for the simulation of an energy-efficient electric vehicle 123

Figure 5.8 ( a) Total distance travelled curve for the design of an electric vehicle and ( b) typical acceleration response curve, and ( c) efficiency calculation characteristics of the proposed PMSM motor at various operating regions .124

Figure 5.9 Illustration of ( a) torque, ( b) torque angle, ( c) q-axis current, ( d) d-axis current, ( e) steady-state armature current and ( f) flux linkage for a PWM controller when dc bus voltage Vdc= 200 V, Ld= 0.0025 H and Lq= 0.002 H .126

xviii List of Figures

Figure 5.10 Dynamic behaviour investigation of ( a) torque, ( b) torque

angle, ( c) q-axis current, ( d) d-axis current, ( e) three-phase

stator current, ( f) steady-state armature current and

( g) flux linkage when hysteresis window size is reduced in

a  torque-controlled PMSM drive 127

Figure 5.11 Dynamic characteristics of ( a) torque, ( b) torque angle,

( c) q-axis current and ( d) steady-state current of a

torque-controlled PMSM drive under stator resistance variation 128

Figure 5.12 Demonstration of dynamic response of ( a) torque, ( b) q-axis

current and ( c) flux linkage during demagnetization in this

proposed torque-operated drive 129

Figure 5.13 Representation of torque pulsations vs hysteresis window band 129

Figure 5.14 Illustration of PWM carrier frequency of the inverter vs

hysteresis window band 130

Figure 5.15 Real-time response of generated emf, armature current

on no-load and on-load operation of a permanent magnet

synchronous motor torque drive 131

Figure 5.16 Real-time comparative analysis of ( a,b) q-axis current,

( c,d) electromagnetic torque, ( e,f) FFT analysis of torque

ripple and ( g,h) THD analysis of current waveform using a

hysteresis current controller and a PWM current controller 132

Figure 5.17 Comparative analysis of current THD and torque ripples in

hysteresis current control and PWM current control 133

List of Tables

Table 2.1 Representation of Different Pole Voltages ( vao, vbo and vco) for

Various Switching Combinations 21

Table 2.2 Representation of Three Armature Phase Voltages for Various Switching Combinations 21

Table 2.3 Simulation Parameters 28

Table 2.4 Technical Details of PMSM Machine under Test 43

Table 3.1 Comparative Time Domain Analysis 73

Table 3.2 Proposed Fuzzy Rules for Both Input and Output Function 76

Table 3.3 Comparative Controller Performance Analysis in Time Domain 79

Table 3.4 Comparative Performance of Frequency Domain Analysis 79

Table 4.1 Switching Combinations for the Generation of Switching Pulses 86

Table 4.2 Electric Scooter Parameter 91

Table 4.3 Technical Details of the Inverter Circuit 101

Table 5.1 Simulation Parameters of the System 118

Table 5.2 Electric Scooter Parameter 123

Table 5.3 Technical Specifications of PMSM Motor under Test 131

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Preface

To reduce the emissions of greenhouse gasses and maintain environmental ability, electric vehicles play a vital role in a modern energy-efficient environment Permanent magnet synchronous motors ( PMSMs) are widely employed in electric vehicle technology due to their high dynamic response, better torque-speed charac-teristics, noiseless operation, high power density, high efficiency and power factor as compared to other conventional motor drives This research work demonstrates the development of various control strategies and illustrates the dynamic performance intensification of the PMSM drive For the satisfactory as well as energy-efficient operation of a typical electric drive system, control strategy plays a challenging role Additionally, to ensure faster dynamic behaviour and flexibility in control under vari-ous operating conditions, performance of a PMSM drive has been investigated in this work Moreover, control strategies have been executed through mathematical model-ling and illustration of several case studies for optimal operation

sustain-First, the book confers an improved control strategy based on self-controlled operation of a PMSM drive under various operating conditions In this area, illustra-tion of dynamic performance intensification of a PMSM operated through a pulse width modulation ( PWM)-controlled voltage source inverter ( VSI) which synchro-nizes with the rotor position information is established Moreover, it is observed that by few modifications of the position sensor circuitry, nearly sinusoidal arma-ture phase currents result, which generates less torque ripples Subsequently, three input parameters such as dc bus voltage, load torque and sensor angle are considered

to establish the typical dynamic behaviour of the drive system An effective speed control strategy of the drive system by the variation of dc bus voltage is achieved, which is analogous to armature voltage control of a separately excited dc machine

In a self-controlled PMSM, the space angle between the field mmf ( magneto motive force) and the armature mmf can be considered in various switching instants of the inverter to ensure position estimation Furthermore, a newly introduced performance indicator, i.e sensor lead angle, is proposed due to the angular displacement between the field mmf and armature mmf at different switching combinations The different dynamic behaviour of the PMSM machine is determined and is eventually simulated through MATLAB® simulation for various sensor lead angles with unanticipated variation in the load

Subsequently, the closed- loop-based strategy of a PMSM drive using various classical controllers and fuzzy logic controllers is investigated through various case studies for optimal operation A substantial comparative performance optimization

is carried out between the PI, PID, lead, lead-lag and fuzzy logic controllers of a plified as well as detailed mathematical model of a PMSM drive The overall struc-ture of the PMSM drive is separated into two loop control structures: inner current loop and outer speed loop All the necessary performance indices of the proposed PMSM drive system are tested in a MATLAB®/Simulink® environment Moreover, the performance of a fuzzy logic speed-controlled PMSM drive as compared to all classical controllers provides better dynamic as well as steady-state performance with

sim-xxii Preface

reduced torque ripples A fuzzy-controlled PWM-operated PMSM drive ensures the nearly zero steady-state speed error in this approach Finally, the performance of a fuzzy-controlled closed-loop PMSM drive is investigated in the real-time set-up and necessary dynamic responses are carried out

Furthermore, an improved PWM-operated buck- converter-fed VSI acting as a current source inverter ( CSI) is capable of minimizing the voltage and current ripples significantly compared to a conventional VSI designed in the real-time set-up By using this converter control strategy, an efficient current control technique is estab-lished, which protects the PMSM motor from sudden overloading In a typical light electric vehicle application, this method is the best suited

Lastly, modelling and comparative dynamic analysis of a field-oriented controlled PMSM torque drive using a hysteresis current controller and a PWM-operated current controller is established To illustrate the concept, torque and mutual flux, linkages are applied as external inputs and the speed of the machine is kept fixed Moreover, the magnitude of torque angle as well as stator current reference are con-trolled through the machine dynamics In hysteresis current, controllers with a large hysteresis band current ripple and the torque pulsations are prominent at higher car-rier frequencies of the inverter Afterwards, a PWM current controller with identical operating conditions is proposed for such reduction of torque pulsation as well as ripples in the current waveform Additionally, a relationship with the magnitude of torque pulsations, PWM carrier frequency and the hysteresis window size are also achieved through various case studies Finally, various feasible results are presented through MATLAB simulation and the necessary hardware implementation to justify the comparative assessment of the proposed controllers for dynamic performance analysis in energy-efficient electric vehicles

MATLAB® is a registered trademark of The MathWorks, Inc For product information,please contact:

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Acknowledgements

We are grateful to the honourable Director, Prof Bibhuti Bhusan Biswal, for his encouragement and good wishes for our research work We are also very much obliged to Dr Sanjay Debbarma, HOD of Electrical Engineering Department, NIT Meghalaya, for providing all the possible suggestions towards this work

We are especially indebted to Prof Pradip Kumar Sadhu [IIT (ISM) Dhanbad],

Dr Praveen Kumar (IIT Guwahati), Dr Supriyo Das, Dr Anup Dandapat and

Dr Kishore Debnath for their technical help and valuable suggestions during the work We are also grateful to all the faculty members of the EE Department, NIT Meghalaya, for their useful suggestions and encouragements

We would like to show our gratitude to Prof Valentina Emilia Balas, Aurel Vlaicu University of Arad, Romania and Prof P Sanjeevikumar, Aalborg University, Denmark, for their invaluable discussions and support in the field to achieve some important goals of the research study

We would like to thank all the faculty and staff members of the Siliguri Institute of Technology, Siliguri, India, especially Prof Jayanta Bhusan Basu, Prof Mitul Ranjan Chakraborty, Prof Sanjukta Dey, Dr Subhojit Dawn, Prof Koushik Chatterjee, Prof Indrajit Koley, Mr Ramkrishna Mallick and Dr Suman Koner (Jalpaiguri Govt Engineering College) for providing their direct/indirect support during the entire work We truly thank Mr Tapan Das (M/S Anjali Enterprise) for extending his sup-port to develop the hardware prototype

We especially appreciate the help, acceptance and advice of many individuals without whom this opportunity would never have become fruitful Professors, staff members, present colleagues and friends of the NIT Meghalaya and NIT Mizoram have been the source of inspiration and support to pursue scientific and personal growth

We wish to express our special thanks to Hari Charan Nannam, Pratikanta Mishra and Thanikanti Sudhakar Babu for their cooperation throughout this work

Finally, we would like to express our deepest gratitude to our families for their love, patience, encouragement and continuous moral support

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Authors

Chiranjit Sain received his B.Tech in Electrical Engineering from Maulana Abul

Kalam Azad University of Technology, Kolkata, India, and M.Tech in the tion of Mechatronics and Automation Engineering under the Electrical Engineering Department from the National Institute of Technical Teachers Training and Research ( NITTTR), Kolkata, India He completed his Ph.D in Electrical Engineering from the National Institute of Technology Meghalaya, India, in 2019 Presently he is work-ing as an Assistant Professor in the Department of Electrical Engineering at Ghani Khan Choudhury Institute of Engineering & Technology (GKCIET), A Centrally Funded Technical Institute (CFTI) under the Ministry of Education, Government

specializa-of India, Malda, West-Bengal, India He is a member specializa-of the IEEE and an associate member of the Institution of Engineers India Limited His present research inter-ests include sensorless and vector control of permanent magnet motor drives, digital control in power electronics converters, electric vehicles, design and optimization of electrical machines, soft-computing analysis, etc

Atanu Banerjee received his B.E in Power Electronics Engineering from Nagpur

University in 2001 and M.E in Electrical Engineering with specialization in Power Electronics  & Drives in 2008 from Bengal Engineering  & Science University, Shibpur ( Now IIEST, Shibpur) He completed his Ph.D in Electrical Engineering at the Indian School of Mines, ( IIT) Dhanbad, India, in 2013 He worked in industry for almost three years and has academic experience of more than 15 years Presently, he

is an Associate Professor in the Electrical Engineering Department at the National Institute of Technology, Meghalaya His research interests include induction heating and high-frequency switching in power electronics converters, PM motor drives and control, renewable energy, etc He has published a few books and several journal/ conference research papers He has filed two patents to the Government of India Presently, he is working on a few sponsored research projects sanctioned by the Government of India

Pabitra Kumar Biswas completed his B.Tech at the Asansol Engineering College, WBUT, India He received his M.E degree from Bengal Engineering and Science University, West-Bengal, India, and Ph.D in Electrical Engineering from the National Institute of Technology, Durgapur, India He is presently working as

an Assistant Professor and HOD in the Electrical Engineering Department at the National Institute of Technology, Mizoram, India He has published a number of research papers in national/ international conference records/ journals He has about

11 years of academic as well as research experience His research interests include electromagnetic levitation systems, active magnetic bearing, power electronics con-verters and machine drives, renewable energy, etc He has filed two patents to the Government of India Presently, he is guiding a few research scholars in various fields

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i , i qsr dsr q-axis and d-axis armature currents in rotor reference frame

δ , i , e dq dq torque angle, d-q axis currents, d-q axis-induced voltages

ω

δ

i cos S * Flux-producing stator current

acceleration force

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1.1 BACKGROUND AND PROBLEM FORMULATION

An advancement in the permanent magnet materials, concept of integrated industrial electronics and the sophisticated control technique including semiconductor fabrica-tion technology permanent magnet synchronous motor ( PMSM) drives are exten-sively employed in different industrial, commercial and domestic applications The electric motors used in electric vehicles require better torque-speed characteristics to obtain higher operating range and improved efficiency [1] Generally, the character-istics of flux linkage in the air gap and the emf generated in the armature winding, supplied by permanent magnets, exhibit sinusoidal characteristics PMSMs are con-siderably employed in electric vehicle technology due to its high dynamic response, better torque-speed characteristics, noiseless operation, high power density and high efficiency compared with other traditional motors Basically, the design of inverter and advanced control technique play an important role in energy-efficient light elec-tric vehicles In conventional vehicles, fuel consumption and emission of harmful gases lead to the incremental pollution and are hazardous for the society and environ-ment In general, energy efficiency of an electric propulsion system depends on the different losses, harmonic distortion, torque pulsations, noise and vibration due to the production of cogging torque, etc Usage of clean energy sources could be helpful to draw the apprehension of using a vehicle due to environmental concern [2,3].Additionally, PMSM machines are treated as a special kind of electrical machine build up with a standard multi-phase armature mounted on the stator and permanent magnets placed in the rotor In view of the non-appearance of slip ring and brush composition, regular maintenance is getting reduced and robustness also improves

In a PMSM machine, the kind of distribution flux density in the air gap and the corresponding voltage developed in the armature caused by the permanent magnet material appointed reveal sinusoidal response The availability of rare earth mate-rial increases the use of permanent magnet machines in household and commercial applications [4] For PMSMs having sinusoidal back EMF, the inverter is operated

at 180° conduction mode as well as sinusoidal pulse width modulation strategy However, irrespective of the conduction pattern, the power switches are supposed to operate in synchronism with the rotor position to ensure a time-invariant space angle between the permanent magnet rotor magneto motive force (mmf) and the armature mmf, at least on an average basis, resulting in a unidirectional torque

The permanent magnet synchronous machines are widely categorized on the nature of the field flux direction as follows:

1 Radial field: the direction of the flux is along the radius of the machine

2 Axial field: the direction of the flux is parallel to the shaft of the rotor

DOI: 10.1201/9781003189558-1

2 Control Strategies of Motor Drive

The radial field machines are familiar and the axial field machines are existent in recent applications due to its power density and acceleration Moreover, the magnets can be placed in several ways on the rotor Higher power density synchronous motor has surface-permanent magnets with radial distribution generally for application, whereas the interior-magnet machines are employed for high-speed application

1.2 REVIEW OF MATHEMATICAL MODELLING

AND OPEN- LOOP-BASED CONTROL STRATEGY

OF A SELF-CONTROLLED PMSM DRIVE

Mathematical modelling is used to determine the analytical representation to observe the dynamic behaviour under various operating conditions This work discusses the development of a mathematical model of a self-synchronous PMSM supplied from a multi-phase inverter This model brings out the basic understanding about:

i How a machine, primarily synchronous in nature, is made to behave lar to a conventional dc machine, without the presence of the mechanical commutator-brush assembly

ii How a machine, primarily synchronous in nature, can be made to run as a variable speed drive with varying load torques without getting out of step iii How speed control can be implemented in a way equivalent of a traditional

dc machine – either by varying the dc link voltage ( Vdc) or by the variation

in equivalent conceptual ‘ brush’ position with respect to the rotor frame, defined by the variable ‘ sang’ in this discussion

The function of the mechanical commutator, here, is taken up by the power electronic three-phase bridge inverter, whose devices are operated in a self-synchronism manner with the rotor position Consequently, the frequency of the currents and/ or voltages in each armature phase of the PMSM is dictated by the machine speed rather than the opposite, which generally occurs in a conventional synchronous machine [5] This is the true essence of ‘ self-control or self-synchronous’ operation, whereby the rotor posi-tion dictates the commutation of devices in the armature and hence the frequency of voltage or current in the armature, thereby eliminating all possibilities of the rotor be coming out of step, a problem which used to cause maximum bottleneck for synchro-nous machine operations If a conventional dc machine operation is deeply thought about, it can be appreciated that, there also, the mechanical commutator performs the same role, i.e it effects a rotor position-dependent commutation in the armature

1.2.1 L iterature S urvey

A robust method to detect the initial rotor position estimation as well as identification

of magnetic polarity using zero-sequence voltage was reported [6] Zhang et al [7] presented one modified rotor position assessment strategy of a PMSM using reduced resolution hall-effect sensors One asymmetric PWM method for rotor position esti-mation in a low-speed IPMSM machine using current-controlled voltage source con-verter was discussed by de Belie and Melkebeek [8] A recently reported work [9]

Introduction

demonstrates the open- loop-based development of a self-controlled PMSM drive under various operating conditions In this work, a suitable method for the speed con-trol of a PMSM motor, such as variation of dc link voltage, has been established

A current-controlled topology on a fully integrated FPGA-controlled synchronous motor drive fitted with a resolver position sensor was reported by Idkhajine et  al [10] An advanced switching combination based on SV-PWM control strategy to vary the switching frequency extensively for a PMSM machine was demonstrated by Choudhury et al [11] A fruitful control strategy for six-step operation to enhance the dynamic behaviour related with current control scheme of a PMSM was discussed

by Kwon et al [12] Peng and Xi [13] presented one incremental predictive current control technique where back emf item is eliminated with faster response mode An improved rotor position estimation method by detection of stator currents magnitude without injecting high-frequency voltage signal under wide range of operation in

an interior PMSM machine was reported by Tseng et al [14] From the literature, it seems that for such self-synchronous operation of a VSI/ CSI-controlled PMSM, rotor position control as well as economic and simplified design of the converter control circuitry is limited Moreover, for the prediction of faster dynamic behaviour of a PMSM, using such adjustment of field and armature mmf space vector in accordance with the inverter switching combinations has not been reported earlier

1.3 REVIEW OF CLOSED- LOOP-BASED CONTROL

STRATEGY OF A PMSM DRIVE

Any system that employs feedback is classified as closed-loop control system The role of the feedback is to initiate decisions about any changes to the control signal Moreover, closed-loop systems naturally work at a fixed frequency The basic objec-tive for the development of closed-loop control strategy is to design the current con-trol loop and the speed control loop using mathematical modelling Additionally, the role of controller is to reduce the system error for a longer operation of the system and

to optimize the system performance An automated closed-loop PMSM drive could

be obtained by designing a speed controller, where the information about the ence speed and the actual speed should be always available [15] This speed control-ler may then act on a front-end power electronic converter whose output would be a controlled dc voltage ( Vdc)

1 A closed-loop automated speed control of a PMSM drive can be done through the same VSI, which feeds the PMSM, i.e no separate front-end power electronic converter needs to be employed

2 Pulse width modulation ( PWM) strategy could be adopted to the self-controlled multi-phase feeding the PMSM, for the elimination of lower order harmonics from the harmonic spectrum of the armature currents, gen-erating lesser toque ripple

This topic focuses on the configuration of a model of an automated closed-loop PMSM drive incorporating a self-synchronous VSI feeding the machine, where the

4 Control Strategies of Motor Drive

inverter devices are switched in synchronism with rotor position and at the same time according to a sinusoidal pulse width modulation ( SPWM) technique For the development of such a model, the strategy adopted was to maintain the dc component

of the d-axis armature voltage ( i.e dc component of Vds) to zero

A standard closed-loop control structure of a typical PMSM drive system tion of current control loop as well as speed control loop takes a major role for such optimal operation Any closed- loop-based control structure comprises feedbacks An analytical model for such development of two loop control structure of a PMSM drive is discussed in this section In this proposed model of PMSM drive, PI con-troller is taken in current control loop and fuzzy adaptive controller with simplified fuzzy rules is taken in outer speed control loop [16] The gain and the reset time of the PI current controller are obtained analytically with reference to the parameters

forma-of the proposed developed model In this detailed model, the output ( error) forma-of inner

PI controller is fed to the SPWM inverter to which the actual rotor speed is applied

1.3.1 L iterature S urvey

A hybrid technique is comprised of two degrees of freedom if a PID controller was discussed for high-performance applications [17] In this method, some optimization tools like genetic algorithm and artificial neural network are used for such tuning operation A GSA ( gravitational search algorithm)-based robust intelligent controller design for such a wide range of operations in an electromagnetic levitation system was reported [18] A hybrid technology-based fuzzy PI controller in a vector-controlled PMSM drive was proposed to improve the steady-state behaviour based on various switching functions [19] A fuzzy logic rule-based adaptive PID controller design for enhancing the dynamic performance of a process was discussed [20] A robust fuzzy PI controller design for non-linear model of a PMSM was reported [21] In this method, asymptotic stability has been confirmed for a closed-loop structure

A mamdani interface-based computational aspect of a non-linear fuzzy PID troller was observed [22] Basically, in this model, three input variables are consid-ered to determine the stability of a system A torque ripple minimization method was reported based on optimum current calculation topology for a non-sinusoidal PMSM machine [23] A wide range of controlled new membership function-based fuzzy PID control techniques for such optimal operation in a non-linear system were discussed [7]

con-1.3.2 r eview of f uzzy L ogic -c ontroLLed PwM-o Perated PMSM d rive

A fuzzy logic-based fault diagnosis method in a three-phase PMSM drive for ing the reliability was discussed by Yan et  al [24] Basically, in this method, the kind of intermittent faults in power switches was measured In Singh et al [25], the design of a hybrid fuzzy controller and a PI speed controller of a vector-controlled PMSM drive using DSP controller was reported In this study, hybrid speed control-ler is observed satisfactorily for high level of performance under different operating conditions Ramesh et  al [26] presented a suitable method for reducing flux and torque ripples for a DTC-controlled drive using fuzzy logic controller and PI speed

of PMSM using the neutral point method at zero speed regions was found by Chen and Huang [30] In this method, inductance of the coils is affected by the rotor flux to detect the position of the rotor Ameur et al [31] described the design of a buck-type CSI and its application to position sensorless control A fuzzy logic-based modified direct torque control of a PMSM was proposed by Mehta et al [32] to control the instantaneous torque A fuzzy logic-operated blended control approach to improve the robustness and energy management topology in a hybrid electric vehicle was proposed by Meng et al [33] A high-frequency transformer-operated current source inverter-fed electric drive was addressed by Lu et al [34] for hybrid electric vehicles.

1.4 DEVELOPMENT OF DIFFERENT CONTROL

STRATEGIES OF A PMSM DRIVE

Electric propulsion system is one of the vital components in an electric vehicle that comprises a typical electric drive, an energy storage system and a transmission body High-energy density and faster dynamic response are to be expected from a typi-cal drive system in electric propulsion The design of an electric propulsion system should be compatible to match the vehicle requirements such as optimum accelera-tion, high torque, efficient speed and gradability [35] In general energy conversion efficiency of electric propulsion, systems vary upon various machine losses, har-monic distortion, torque pulsations, production of cogging torque, etc Moreover, several research works are continuing to enhance the energy efficiency of the elec-tric vehicles in recent days Few usual factors are considered for the improvement of electric motor energy saving in industrial sectors One of the vital solutions was to operate several small motors having the nearest power rating instead of using single large unit, secondly to build high-efficiency electric motors by enhancing various design topologies as well as better classification of materials used and finally the maximization of efficiency based on some advanced control strategies in electric motor drives It is well known that efficiency of an electric motor is different at various operating regions to be compatible with the dynamic characteristics, i.e torque-speed nature [36]

The latest technology of the permanent magnet materials such as rare earth nets and samarium cobalt PMSM motors is promisingly adopted in the different industrial and commercial applications Several advantages compared to the con-ventional electrical machines such as high-energy density, greater torque- to-volume

mag-6 Control Strategies of Motor Drive

ratio, compact and robust construction, improved efficiency, etc can be considered

in such high-performance applications Different control strategies such as vector control and flux weakening control play a challenging role in different industrial drives The prime motivation for the development of the PMSM in electric propulsion

is the harmonics torque pulsations generated through the non-sinusoidal flux form around the air gap Such applications as speed control technique in conveyor system presence of torque ripples are truly unacceptable and must be minimized Generation of torque pulsations causes an instant torque that pulsates intermittently with the corresponding variation in rotor position estimation Generally, permanent magnet materials are characterized based on the energy density, and the nature of resistance to demagnetize truly affects the behaviour of the permanent magnet syn-chronous machine [37] Among the permanent magnet materials, neodymium iron boron magnets are the favourable rare earth magnets employed in permanent magnet motors in present days as they possess superior B-H characteristics since the magni-tude of torque is measured with proportion to the current taken in the rotor reference frame Various current control strategies have been adopted in the PMSM drives to confirm that stator currents identify their respective reference value of currents In case of hysteresis, current control technique compared with other control strategies employs sophisticated current tracking behaviour and removes the use of feedback loop compensation Moreover, the range of control and sensitivity of the machine parameters play a crucial role for such optimal operation of the drive system under such circumstances [38]

Introduction

the inoculation of fifth and seventh harmonic components of the stator currents A proportional resonant controller in the frequency region through an adaptive control method for reduction of torque ripples in a PMSM was reported by Vafaie et al [36] Brock et al [40] described an approach for the compensation torque harmonics as well as flux harmonics through angular spectral analysis A hysteresis current control algorithm was demonstrated by Cao et al [41] for a field-oriented control operation

of a closed-loop PMSM drive A faster speed response while sustaining a better rent tracking capability was ensured in this proposed method Kwon and Sul [42] discussed an effective flux-weakening algorithm in a speed-controlled PMSM drive for a light electric vehicle since this method was limited to discussion about the con-trol of torque angle as well as flux linkage through an input in the stator A modified direct torque control strategy of a PMSM motor was reported by Huang et al [43] to use in hydraulic excavator system With the help of this strategy, a notable reduction

cur-in the dc voltage cur-interruption on the optimal torque operation was achieved

1.5 SOLAR-POWERED PMSM DRIVE SMART ELECTRIC

VEHICLE FOR SUSTAINABLE DEVELOPMENT

With the advancement of industrial engineering, a holistic interpretation for the vation and growth of the latest technologies has been enriched In the present years, the utilization of information and communication technology ( ICT) has reflected the industrial process and the production system in a significant manner [44] Basically, industrial engineering introduces a new scientific and industrial planning that uses information technology as well as industrial automation to enhance the overall indus-trial productivity Society and mankind have been promisingly aware regarding the destroying effect on the atmosphere Electric vehicles have been distinguished to play

inno-a vitinno-al role in retrieving the binno-alinno-ance Presently, the green energy sources generinno-ate lower than 10% of the energy utilized in the electric grid, since majority of the elec-trical energy utilized for charging electric vehicles is generated from burning fossil fuels, such as coal, gas and oil, at the various generating units [45] The transformation

in the global atmosphere is one of the major environmental concerns in present day’s scenario The only initiative to overcome this critical hazardous effect is to reduce the level of greenhouse gases In many developing countries, several measures have been adopted to maintain the emission of harmful gasses such as carbon dioxide, carbon monoxide and nitrous oxides to a sustainable limit The overall economic growth and environmental sustainability of a country depends on the utilization of electric power Therefore, to meet with the energy-efficient and clean energy environment, utilization

of renewable energy sources is one of the promising interests throughout the world Out of the entire non-conventional sources of energy, solar is one of the economic,

e nvironment-friendly, easy maintenance options and the largest energy sources in view of the renewable energy sector In conventional vehicles, fuel consumption and emission of harmful gases lead to the incremental pollution and are hazardous for the society and environment Basically, the energy efficiency of an electric propul-sion system depends on the different losses, harmonic distortion, torque pulsations, noise, vibration, etc [40] Usage of clean energy sources could be helpful to draw the

8 Control Strategies of Motor Drive

apprehension of using a vehicle due to environmental concern Energy consumption

of an electric vehicle is solely dependent on aerodynamic details It is obvious that the more aerodynamic it is, the lower the vehicle energy consumption At high-speed operation of the modern electric vehicles, aerodynamics is much important for elec-trical energy consumption and utilization Depending on the designing aspect, the mass of the vehicle, aerodynamic drag, rolling resistance, motor/ engine efficiency, and transmission efficiencies need to be considered while expecting optimum energy efficiency Hence, the transmission efficiency of a modern electric vehicle can be enhanced by incorporating an energy-efficient electric motor, thus eliminating the use of the gearbox and clutch as the electric motor generates torque from stand-still onwards In case of an energy-efficient vehicle, the efficiency for the conver-sion of electrical energy provided on vehicle charging at the wheels varies nearly by 45%–55% The optimum efficiency for a merchant solar cell is presently about 16% and may lower to approximately 13% while surrounded The maximum power that can be obtained from solar dissipation on the earth’s surface is 1000 Wm−2, which is generally smaller because of the presence of cloud and dust in the environment [46].With the advancement of IoT ( Internet of Things) technology, electric vehicles can be promisingly established as an advanced type of mobile intelligent power con-sumption device In typical smart grid technology, electric vehicles can be used as energy storage protocol Smart grid technology can provide intelligent monitoring and a wide area communicating the network with greater control on all aspects of operations [41] As a result, charging system, monitoring system, billing system and entire data collection technology of a typical electric vehicle can be transformed into a smart system Hence, this robust and intelligent control technology using IoT tools can be incorporated in a solar-powered electric vehicle for enhancing the envi-ronmental sustainability and future demand in a smart city PMSM machines are vastly employed in electric vehicle technology due to its high dynamic response, better torque-speed characteristics, noiseless operation, high power density and high efficiency unlike other conventional motors Basically, the design of power electronic converter and sophisticated control technique plays an important role in energy-efficient electric vehicles Therefore, different control strategies of PMSM drives have been addressed towards the application of an electric vehicle in a modern energy-efficient environment [47]

1.5.1 L iterature S urvey

Robinson et al [48] highlighted the impact of recharging attitude of an electric cle driver and also the effect in the current policy of recharging demand profiles in north east of England The authors are also described about the required financial supports and possible smart tolls for greater management of vehicle recharging unit for maximum demand Richardson [49] discussed about the recent developments of electric vehicles, the integration of renewable energy and electric grid In this article, the economic and environmental impacts of the grid for electric vehicles are also discussed Daziano and Chiew [50] pointed out the invention of electric vehicles as

vehi-an alternative solution for the sustainable trvehi-ansportation system In this article, one generalized discrete model for the purchasing an electric vehicle is proposed and the

Introduction

corresponding data analysis is also introduced Ewing and Sarigöllü [51] discussed about the protocol for consumer choices in clean fuel vehicles against the conven-tional vehicles employing the discrete choice methodology They also established three market segments for achieving the target for such clean fuel vehicles Taylor

et al [52] demonstrated about the analytical framework to monitor the influence of plug-in electric vehicles on the functioning of distribution systems Basically the introduction of plug-in electric vehicles on one utility distribution feeder is summa-rized Galus et al [53] discussed some smart management systems to reduce the pos-sible congestion issues in energy networks for the amalgamation of plug-in electric vehicles Garimella et al [54] proposed the concept of electromechanical heat cre-ation in a lithium ion battery The amount of heat generated in this process is a robust component of current and temperature and the entropic function in charge depletion

is analysed Glerum et  al [55] proposed a dynamic discrete-continuous model of car proprietorship and its use In this article, the methodology used to describe the model can specify the annual travelled distance, type of fuel, car state, ownership status, etc Parks et al [56] described some efficient methodologies about cost analy-sis, modelling approaches, environmental needs and security interests to evaluate the performance of plug-in hybrid electric vehicles in utility system operations Soares

et al [57] discussed some stochastic solutions for the future charging of electric cles and also addressed a tool based on Monte Carlo method for distribution of grid planning Zakariazadeh et al [58] developed one fruitful method for the operational planning of an integrated distribution system Moreover in this solution, scheduling

vehi-of electric vehicles and non-conventional generators are integrated to suppress the negative effects associated with the renewable generation

1.6 SMART TECHNOLOGY-BASED SOLAR-POWERED

ELECTRIC VEHICLE

With the emerging trends of IoT technology and the renewable energy integration, electric vehicles play a significant role in the sustainable development of the envi-ronment Self-monitoring analysis and reporting technology ( Smart) has been an innovative interest in the industries as well in research institutions for such strong foundation and robust control To meet the latest vision, a huge change in the power supply infrastructure and traffic systems need to be incorporated In fact, drivers are supposed to get the reliability that they will be able to conveniently recharge their vehicle wherever they are [59] The required closely meshed network of charging stations will only be obtained at sustainable cost with very smart and cost-effective electric charging systems that can be installed anywhere Electricity is available everywhere, so that electric mobility can be configured on a sound infrastructural basis The charging stations are only energized after a registered user has activated the charging function Thus, there is no danger of live cables being exposed even when a Smart charging station is destroyed or knocked over in an accident The pro-posed charging station can also be installed to display additional information such as road map and tourist guidance in nearby places A typical layout representation for a solar-powered Smart electric vehicle is depicted in Figure 1.1

10 Control Strategies of Motor Drive

Recently SIEMENS Technology Solution has proposed and designed Smart-based charging solution for a modern electric vehicle depicted in Figure 1.2 The real-time image of a solar-powered Smart electric vehicle developed by the Mobility House

is represented in Figure 1.3 Here, solar panels have been utilized for the charging purpose in the proposed electric vehicles and some novel IoT tools are incorporated for such sophisticated control and environment friendliness [60] In a typical smart city application, integration of an electric grid and the vehicles can be an efficient approach for security, economy and energy storage environment

In Figure 1.4, a typical IoT-based architecture for a Smart electric vehicle is resented Generally, the entire architecture is comprised of several elements such

rep-as different sensors ( motion sensor, optical sensor and smart sensor), network ing wireless connectivity for communication, cloud computing, data storage devices and some security as well as safety devices [61] Moreover, the IoT technology has been integrated in electric vehicles in different smart cities to monitor and implement

FIGURE 1.1 Layout representation of a solar-powered smart electric vehicle ( The Mobility

House.)

FIGURE  1.2 Smart technology-based charging solution for a modern electric vehicle

( SIEMENS Technology solution.)

Introduction

FIGURE 1.3 Image of a solar-powered smart electric vehicle ( The Mobility House.)

FIGURE  1.4 Internet of Things ( IoT)-based architecture for a smart electric vehicle

( Internet of Things for Smart Cities; Zanella et al [62])