Skip to main content

Save up to 20% on Elsevier print and eBooks with free shipping. No promo code needed.

Save up to 20% on print and eBooks.

Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management

1st Edition - September 1, 2024

Authors: Jili Tao, Zhang Ridong, Ma Longhua

Language: English
Paperback ISBN:
9 7 8 - 0 - 4 4 3 - 1 3 1 8 9 - 9
eBook ISBN:
9 7 8 - 0 - 4 4 3 - 1 3 1 9 0 - 5

Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management presents the state-of-the-art in hybrid electric vehicle system modeling and management. With a… Read more

Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management

Purchase options

LIMITED OFFER

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code is needed.

Institutional subscription on ScienceDirect

Request a sales quote
Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management presents the state-of-the-art in hybrid electric vehicle system modeling 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. It 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.