Artificial intelligent techniques for electric and hybrid electric vehicles

Artificial intelligent techniques for electric and hybrid electric vehicles

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Detalles Bibliográficos
Otros Autores: Himavathi, S. (-), Holm-Nielsen, Jens Bo, A., Chitra, Padmanaban, S.
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken : Scrivener Publishing 2020.
Colección:Wiley ebooks.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b43379321*spi
Tabla de Contenidos:
  • 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.

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