Artificial intelligent techniques for electric and hybrid electric vehicles / edited by Chitra A., P. Sanjeevikumar, Jens Bo Holm-Nielsen and S. Himavathi.
Contributor(s): Himavathi, S
| Holm-Nielsen, Jens Bo | A., Chitra | Padmanaban, S.
Material type: 
BookPublisher: Hoboken : Scrivener Publishing, 2020Description: 1 online resource (278 p.).ISBN: 9781119682035; 1119682037; 9781119682011; 1119682010.Subject(s): Artificial intelligence -- Engineering applications | Electric vehicles -- Data processing | Artificial intelligence -- Engineering applicationsGenre/Form: Electronic books.Additional physical formats: Print version:: Artificial Intelligent Techniques for Electric and Hybrid Electric VehiclesDDC classification: 620.002856/3 Online resources: Wiley Online Library Description based upon print version of record.
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 IoT-Based Battery Management System for Hybrid Electric Vehicle -- 1.1 Introduction -- 1.2 Battery Configurations -- 1.3 Types of Batteries for HEV and EV -- 1.4 Functional Blocks of BMS -- 1.4.1 Components of BMS System -- 1.5 IoT-Based Battery Monitoring System -- References -- Chapter 2 A Noble Control Approach for Brushless Direct Current Motor Drive Using Artificial Intelligence for Optimum Operation of the E -- 2.1 Introduction -- 2.2 Introduction of Electric Vehicle
2.2.1 Historical Background of Electric Vehicle -- 2.2.2 Advantages of Electric Vehicle -- 2.2.2.1 Environmental -- 2.2.2.2 Mechanical -- 2.2.2.3 Energy Efficiency -- 2.2.2.4 Cost of Charging Electric Vehicles -- 2.2.2.5 The Grid Stabilization -- 2.2.2.6 Range -- 2.2.2.7 Heating of EVs -- 2.2.3 Artificial Intelligence -- 2.2.4 Basics of Artificial Intelligence -- 2.2.5 Advantages of Artificial Intelligence in Electric Vehicle -- 2.3 Brushless DC Motor -- 2.4 Mathematical Representation Brushless DC Motor -- 2.5 Closed-Loop Model of BLDC Motor Drive -- 2.5.1 P-I Controller & I-P Controller
2.6 PID Controller -- 2.7 Fuzzy Control -- 2.8 Auto-Tuning Type Fuzzy PID Controller -- 2.9 Genetic Algorithm -- 2.10 Artificial Neural Network-Based Controller -- 2.11 BLDC Motor Speed Controller With ANN-Based PID Controller -- 2.11.1 PID Controller-Based on Neuro Action -- 2.11.2 ANN-Based on PID Controller -- 2.12 Analysis of Different Speed Controllers -- 2.13 Conclusion -- References -- Chapter 3 Optimization Techniques Used in Active Magnetic Bearing System for Electric Vehicles -- 3.1 Introduction -- 3.2 Basic Components of an Active Magnetic Bearing (AMB) -- 3.2.1 Electromagnet Actuator
3.2.2 Rotor -- 3.2.3 Controller -- 3.2.3.1 Position Controller -- 3.2.3.2 Current Controller -- 3.2.4 Sensors -- 3.2.4.1 Position Sensor -- 3.2.4.2 Current Sensor -- 3.2.5 Power Amplifier -- 3.3 Active Magnetic Bearing in Electric Vehicles System -- 3.4 Control Strategies of Active Magnetic Bearing for Electric Vehicles System -- 3.4.1 Fuzzy Logic Controller (FLC) -- 3.4.1.1 Designing of Fuzzy Logic Controller (FLC) Using MATLAB -- 3.4.2 Artificial Neural Network (ANN) -- 3.4.2.1 Artificial Neural Network Using MATLAB -- 3.4.3 Particle Swarm Optimization (PSO)
3.4.4 Particle Swarm Optimization (PSO) Algorithm -- 3.4.4.1 Implementation of Particle Swarm Optimization for Electric Vehicles System -- 3.5 Conclusion -- References -- Chapter 4 Small-Signal Modelling Analysis of Three-Phase Power Converters for EV Applications -- 4.1 Introduction -- 4.2 Overall System Modelling -- 4.2.1 PMSM Dynamic Model -- 4.2.2 VSI-Fed SPMSM Mathematical Model -- 4.3 Mathematical Analysis and Derivation of the Small-Signal Model -- 4.3.1 The Small-Signal Model of the System -- 4.3.2 Small-Signal Model Transfer Functions -- 4.3.3 Bode Diagram Verification -- 4.4 Conclusion
Includes bibliographical references and index.
John Wiley and Sons Wiley Frontlist Obook All English 2020
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