Electric vehicles are changing transportation dramatically and this unique book merges the many disciplines that contribute research to make EV possible, so the reader is informed about all the underlying science and technologies driving the change. An emission-free mobility system is the only way to save the world from the greenhouse effect and other ecological issues. This belief has led to a tremendous growth in the demand for electric vehicles (EV) and hybrid electric vehicles (HEV), which are predicted to have a promising future based on the goals fixed by the European Commission's…mehr
Electric vehicles are changing transportation dramatically and this unique book merges the many disciplines that contribute research to make EV possible, so the reader is informed about all the underlying science and technologies driving the change.
An emission-free mobility system is the only way to save the world from the greenhouse effect and other ecological issues. This belief has led to a tremendous growth in the demand for electric vehicles (EV) and hybrid electric vehicles (HEV), which are predicted to have a promising future based on the goals fixed by the European Commission's Horizon 2020 program.
This book brings together the research that has been carried out in the EV/HEV sector and the leading role of advanced optimization techniques with artificial intelligence (AI). This is achieved by compiling the findings of various studies in the electrical, electronics, computer, and mechanical domains for the EV/HEV system. In addition to acting as a hub forinformation on these research findings, the book also addresses the challenges in the EV/HEV sector and provides proven solutions that involve the most promising AI techniques. Since the commercialization of EVs/HEVs still remains a challenge in industries in terms of performance and cost, these are the two tradeoffs which need to be researched in order to arrive at an optimal solution. Therefore, this book focuses on the convergence of various technologies involved in EVs/HEVs. Since all countries will gradually shift from conventional internal combustion (IC) engine-based vehicles to EVs/HEVs in the near future, it also serves as a useful reliable resource for multidisciplinary researchers and industry teams.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Chitra A. received her PhD from Pondicherry University and is now an associate professor in the School of Electrical Engineering, at Vellore Institute of Technology, Vellore, India. She has published many papers in SCI journals and her research areas include PV-based systems, neural networks, induction motor drives, reliability analysis of multilevel inverters, and electrical vehicles. Sanjeevikumar Padmanaban obtained his PhD from the University of Bologna, Italy, in 2012, and since 2018, he has been a faculty member in the Department of Energy Technology, Aalborg University, Esbjerg, Denmark. He has authored more than 300 scientific papers. Jens Bo Holm-Nielsen currently works at the Department of Energy Technology, Aalborg University and is Head of the Esbjerg Energy Section. He has executed many large-scale European Union and United Nations projects in research aspects of bioenergy, biorefinery processes, the full chain of biogas and green engineering. He has authored more than 100 scientific papers. S. Himavathi received her PhD degree in the area of fuzzy modelling from Anna University, Chennai, India in 2003. Currently, she is a professor in the Department of Electrical and Electronics Engineering, Pondicherry Engineering College, Pondicherry, India.
Inhaltsangabe
Preface xiii
1 IoT-Based Battery Management System for Hybrid Electric Vehicle 1 P. Sivaraman and C. Sharmeela
1.1 Introduction 1
1.2 Battery Configurations 3
1.3 Types of Batteries for HEV and EV 5
1.4 Functional Blocks of BMS 6
1.4.1 Components of BMS System 7
1.5 IoT-Based Battery Monitoring System 11
References 14
2 A Noble Control Approach for Brushless Direct Current Motor Drive Using Artificial Intelligence for Optimum Operation of the Electric Vehicle 17 Upama Das, Pabitra Kumar Biswas and Chiranjit Sain
2.1 Introduction 18
2.2 Introduction of Electric Vehicle 19
2.2.1 Historical Background of Electric Vehicle 19
2.2.2 Advantages of Electric Vehicle 20
2.2.2.1 Environmental 20
2.2.2.2 Mechanical 20
2.2.2.3 Energy Efficiency 20
2.2.2.4 Cost of Charging Electric Vehicles 21
2.2.2.5 The Grid Stabilization 21
2.2.2.6 Range 21
2.2.2.7 Heating of EVs 22
2.2.3 Artificial Intelligence 22
2.2.4 Basics of Artificial Intelligence 23
2.2.5 Advantages of Artificial Intelligence in Electric Vehicle 24
2.3 Brushless DC Motor 24
2.4 Mathematical Representation Brushless DC Motor 25
2.11 BLDC Motor Speed Controller With ANN-Based PID Controller 37
2.11.1 PID Controller-Based on Neuro Action 38
2.11.2 ANN-Based on PID Controller 38
2.12 Analysis of Different Speed Controllers 39
2.13 Conclusion 41
References 42
3 Optimization Techniques Used in Active Magnetic Bearing System for Electric Vehicles 49 Suraj Gupta, Pabitra Kumar Biswas, Sukanta Debnath and Jonathan Laldingliana
3.1 Introduction 50
3.2 Basic Components of an Active Magnetic Bearing (AMB) 54
3.2.1 Electromagnet Actuator 54
3.2.2 Rotor 54
3.2.3 Controller 55
3.2.3.1 Position Controller 56
3.2.3.2 Current Controller 56
3.2.4 Sensors 56
3.2.4.1 Position Sensor 56
3.2.4.2 Current Sensor 57
3.2.5 Power Amplifier 57
3.3 Active Magnetic Bearing in Electric Vehicles System 58
3.4 Control Strategies of Active Magnetic Bearing for Electric Vehicles System 59
3.4.1 Fuzzy Logic Controller (FLC) 59
3.4.1.1 Designing of Fuzzy Logic Controller (FLC) Using MATLAB 60
3.4.4.1 Implementation of Particle Swarm Optimization for Electric Vehicles System 70
3.5 Conclusion 71
References 72
4 Small-Signal Modelling Analysis of Three-Phase Power Converters for EV Applications 77 Mohamed G. Hussien, Sanjeevikumar Padmanaban, Abd El-Wahab Hassan and Jens Bo Holm-Nielsen
4.1 Introduction 77
4.2 Overall System Modelling 79
4.2.1 PMSM Dynamic Model 79
4.2.2 VSI-Fed SPMSM Mathematical Model 80
4.3 Mathematical Analysis and Derivation of the Small-Signal Model 86
1 IoT-Based Battery Management System for Hybrid Electric Vehicle 1 P. Sivaraman and C. Sharmeela
1.1 Introduction 1
1.2 Battery Configurations 3
1.3 Types of Batteries for HEV and EV 5
1.4 Functional Blocks of BMS 6
1.4.1 Components of BMS System 7
1.5 IoT-Based Battery Monitoring System 11
References 14
2 A Noble Control Approach for Brushless Direct Current Motor Drive Using Artificial Intelligence for Optimum Operation of the Electric Vehicle 17 Upama Das, Pabitra Kumar Biswas and Chiranjit Sain
2.1 Introduction 18
2.2 Introduction of Electric Vehicle 19
2.2.1 Historical Background of Electric Vehicle 19
2.2.2 Advantages of Electric Vehicle 20
2.2.2.1 Environmental 20
2.2.2.2 Mechanical 20
2.2.2.3 Energy Efficiency 20
2.2.2.4 Cost of Charging Electric Vehicles 21
2.2.2.5 The Grid Stabilization 21
2.2.2.6 Range 21
2.2.2.7 Heating of EVs 22
2.2.3 Artificial Intelligence 22
2.2.4 Basics of Artificial Intelligence 23
2.2.5 Advantages of Artificial Intelligence in Electric Vehicle 24
2.3 Brushless DC Motor 24
2.4 Mathematical Representation Brushless DC Motor 25
2.11 BLDC Motor Speed Controller With ANN-Based PID Controller 37
2.11.1 PID Controller-Based on Neuro Action 38
2.11.2 ANN-Based on PID Controller 38
2.12 Analysis of Different Speed Controllers 39
2.13 Conclusion 41
References 42
3 Optimization Techniques Used in Active Magnetic Bearing System for Electric Vehicles 49 Suraj Gupta, Pabitra Kumar Biswas, Sukanta Debnath and Jonathan Laldingliana
3.1 Introduction 50
3.2 Basic Components of an Active Magnetic Bearing (AMB) 54
3.2.1 Electromagnet Actuator 54
3.2.2 Rotor 54
3.2.3 Controller 55
3.2.3.1 Position Controller 56
3.2.3.2 Current Controller 56
3.2.4 Sensors 56
3.2.4.1 Position Sensor 56
3.2.4.2 Current Sensor 57
3.2.5 Power Amplifier 57
3.3 Active Magnetic Bearing in Electric Vehicles System 58
3.4 Control Strategies of Active Magnetic Bearing for Electric Vehicles System 59
3.4.1 Fuzzy Logic Controller (FLC) 59
3.4.1.1 Designing of Fuzzy Logic Controller (FLC) Using MATLAB 60
3.4.4.1 Implementation of Particle Swarm Optimization for Electric Vehicles System 70
3.5 Conclusion 71
References 72
4 Small-Signal Modelling Analysis of Three-Phase Power Converters for EV Applications 77 Mohamed G. Hussien, Sanjeevikumar Padmanaban, Abd El-Wahab Hassan and Jens Bo Holm-Nielsen
4.1 Introduction 77
4.2 Overall System Modelling 79
4.2.1 PMSM Dynamic Model 79
4.2.2 VSI-Fed SPMSM Mathematical Model 80
4.3 Mathematical Analysis and Derivation of the Small-Signal Model 86
4.3.1 The Small-Signal Model of the System 86
4.3.2 Small-Signal Model Transfer Functions 87
4.3.3 Bode Diagram V
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