Artificial intelligent techniques for electric and hybrid electric vehicles /

Mostrar otras versiones (1)

Electric 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...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Himavathi, S., Holm-Nielsen, Jens Bo, A., Chitra, Padmanaban, S.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken : Scrivener Publishing, 2020.
Temas:
Artificial intelligence > Engineering applications.
Electric vehicles > Data processing.
Intelligence artificielle > Applications en ingénierie.
Véhicules électriques > Informatique.
Artificial intelligence > Engineering applications
Acceso en línea:Texto completo
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

Ejemplares similares