000 06536cam a2200625 a 4500
001 on1175916330
003 OCoLC
005 20240523125542.0
006 m o d
007 cr un|---aucuu
008 200718s2020 nju ob 001 0 eng d
040 _aEBLCP
_beng
_epn
_cEBLCP
_dYDX
_dDG1
_dOCLCF
_dTOH
_dOCLCQ
_dOCLCO
_dK6U
_dOCLCQ
_dUPM
_dOCLCQ
_dOCLCO
_dOCLCL
019 _a1175675481
020 _a9781119682035
_q(electronic bk. ;
_qoBook)
020 _a1119682037
_q(electronic bk. ;
_qoBook)
020 _a9781119682011
020 _a1119682010
020 _z1119681901
020 _z9781119681908
029 1 _aAU@
_b000068069126
035 _a(OCoLC)1175916330
_z(OCoLC)1175675481
050 4 _aQ335
082 0 4 _a620.002856/3
_223
049 _aMAIN
245 0 0 _aArtificial intelligent techniques for electric and hybrid electric vehicles /
_cedited by Chitra A., P. Sanjeevikumar, Jens Bo Holm-Nielsen and S. Himavathi.
260 _aHoboken :
_bScrivener Publishing,
_c2020.
300 _a1 online resource (278 pages)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
588 0 _aPrint version record.
505 0 _aCover -- 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
505 8 _a2.2.1 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
505 8 _a2.6 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
505 8 _a3.2.2 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)
505 8 _a3.4.4 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
504 _aIncludes bibliographical references and index.
520 _aElectric vehicles/hybrid electric vehicles (EV/HEV) commercialization is still a challenge in industries in terms of performance and cost. The performance along with cost reduction are two tradeoffs which need to be researched to arrive at an optimal solution. This book focuses on the convergence of various technologies involved in EV/HEV. The book brings together the research that is being carried out in the field of EV/HEV whose leading role is by optimization techniques with artificial intelligence (AI). Other featured research includes green drive schemes which involve the possible renewable energy sources integration to develop eco-friendly green vehicles, as well as Internet of Things (IoT)-based techniques for EV/HEVs. Electric vehicle research involves multi-disciplinary expertise from electrical, electronics, mechanical engineering and computer science. Consequently, this book serves as a point of convergence wherein all these domains are addressed and merged and will serve as a potential resource for industrialists and researchers working in the domain of electric vehicles.
590 _aJohn Wiley and Sons
_bWiley Online Library: Complete oBooks
650 0 _aArtificial intelligence
_xEngineering applications.
650 0 _aElectric vehicles
_xData processing.
650 6 _aIntelligence artificielle
_xApplications en ing�enierie.
650 6 _aV�ehicules �electriques
_xInformatique.
650 7 _aArtificial intelligence
_xEngineering applications
_2fast
700 1 _aHimavathi, S.
700 1 _aHolm-Nielsen, Jens Bo.
700 1 _aA., Chitra.
700 1 _aPadmanaban, S.
758 _ihas work:
_aArtificial intelligent techniques for electric and hybrid electric vehicles (Text)
_1https://id.oclc.org/worldcat/entity/E39PCGhfqxRJdqw48gdkY4q9fy
_4https://id.oclc.org/worldcat/ontology/hasWork
776 0 8 _iPrint version:
_aHimavathi, S.
_tArtificial Intelligent Techniques for Electric and Hybrid Electric Vehicles.
_dNewark : John Wiley & Sons, Incorporated, �2020
_z9781119681908
856 4 0 _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781119682035
938 _aProQuest Ebook Central
_bEBLB
_nEBL6261123
938 _aYBP Library Services
_bYANK
_n301373713
994 _a92
_bINLUM
999 _c12723
_d12723