Name: Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management (en Inglés)
Price: 241472.00 ARS
Availability: InStock
Author: Jili Tao Ph.D. Degree From Zhejiang University Hangzhou China In 2007.; Ridong Zhang Ph.D. Degree In Control Science And Engineering From Zhejiang University.; Longhua Ma Ph.D. Degree In Control Science And Engineering From Zhejiang University.
ISBN: 9780443131899

portada Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management (en Inglés)

Formato

Libro Físico

Editorial

Elsevier

Autor

Jili Tao Ph.D. Degree From Zhejiang University Hangzhou China In 2007.; Ridong Zhang Ph.D. Degree In Control Science And Engineering From Zhejiang University.; Longhua Ma Ph.D. Degree In Control Science And Engineering From Zhejiang University.

Idioma

Inglés

N° páginas

346

Encuadernación

Tapa Blanda

ISBN13

9780443131899

N° edición

Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management (en Inglés)

Jili Tao Ph.d. Degree From Zhejiang University Hangzhou China In 2007.; Ridong Zhang Ph.d. Degree In Control Science And Engineering From Zhejiang University.; Longhua Ma Ph.d. Degree In Control Science And Engineering From Zhejiang University. (Autor) · Elsevier · Tapa Blanda

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Reseña del libro "Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management (en Inglés)"

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, this book provides detailed methods, mathematical models, and strategies designed to optimize the energy management of the energy supply module of a hybrid vehicle. This 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, multiobjective optimization, fuzzy Q-learning and Deep Deterministic Policy Gradient (DDPG) algorithms. To help readers apply these management strategies, this 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 modeling 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.

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