Artificial Intelligent Techniques for Electric and Hybrid Electric Vehicles

Chitra A., Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen, S. Himavathi

• Publisher: Wiley-Scrivener
• Year: 2020
• ISBN:
  9781119682004
• Edition: 1
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

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 for information 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.

Table of contents

• Cover
• Table of Contents
• Preface
• 1 IoT-Based Battery Management System for Hybrid Electric Vehicle
• 2 A Noble Control Approach for Brushless Direct Current Motor Drive Using Artificial Intelligence for Optimum Operation of the Electric Vehicle
• 3 Optimization Techniques Used in Active Magnetic Bearing System for Electric Vehicles
• 4 Small-Signal Modelling Analysis of Three-Phase Power Converters for EV Applications
• 5 Energy Management of Hybrid Energy Storage System in PHEV With Various Driving Mode
• 6 Reliability Approach for the Power Semiconductor Devices in EV Applications
• 7 Modeling, Simulation and Analysis of Drive Cycles for PMSM-Based HEV With Optimal Battery Type
• 8 Modified Firefly-Based Maximum Power Point Tracking Algorithm for PV Systems Under Partial Shading Conditions
• 9 Induction Motor Control Schemes for Hybrid Electric Vehicles/Electric Vehicles
• 10 Intelligent Hybrid Battery Management System for Electric Vehicle
• 11 A Comprehensive Study on Various Topologies of Permanent Magnet Motor Drives for Electric Vehicles Application
• 12 A New Approach for Flux Computation Using Intelligent Technique for Direct Flux Oriented Control of Asynchronous Motor
• 13 A Review on Isolated DC–DC Converters Used in Renewable Power Generation Applications
• 14 Basics of Vector Control of Asynchronous Induction Motor and Introduction to Fuzzy Controller
• Index
• End User License Agreement