Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management

Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management
Author :
Publisher : Elsevier
Total Pages : 348
Release :
ISBN-10 : 9780443131905
ISBN-13 : 0443131902
Rating : 4/5 (902 Downloads)

Book Synopsis Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management by : Jili Tao

Download or read book Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management written by Jili Tao and published by Elsevier. This book was released on 2024-06-07 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management presents the state-of-the-art in hybrid electric vehicle system modelling and management. With a focus on learning-based energy management strategies, the book provides detailed methods, mathematical models, and strategies designed to optimize the energy management of the energy supply module of a hybrid vehicle.The book first addresses the underlying problems in Hybrid Electric Vehicle (HEV) modeling, and then introduces several artificial intelligence-based energy management strategies of HEV systems, including those based on fuzzy control with driving pattern recognition, multi objective optimization, fuzzy Q-learning and Deep Deterministic Policy Gradient (DDPG) algorithms. To help readers apply these management strategies, the book also introduces State of Charge and State of Health prediction methods and real time driving pattern recognition. For each application, the detailed experimental process, program code, experimental results, and algorithm performance evaluation are provided.Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management is a valuable reference for anyone involved in the modelling and management of hybrid electric vehicles, and will be of interest to graduate students, researchers, and professionals working on HEVs in the fields of energy, electrical, and automotive engineering. Provides a guide to the modeling and simulation methods of hybrid electric vehicle energy systems, including fuel cell systems Describes the fundamental concepts and theory behind CNN, MPC, fuzzy control, multi objective optimization, fuzzy Q-learning and DDPG Explains how to use energy management methods such as parameter estimation, Q-learning, and pattern recognition, including battery State of Health and State of Charge prediction, and vehicle operating conditions


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