Battery System Modeling

Battery System Modeling provides advances on the modeling of lithium-ion batteries. Offering step-by-step explanations, the book systematically guides the reader through the modeling of state of charge estimation, energy prediction, power evaluation, health estimation, and active control strategies. Using applications alongside practical case studies, each chapter shows the reader how to use the modeling tools provided. Moreover, the chemistry and characteristics are described in detail, with algorithms provided in every chapter. Providing a technical reference on the design and application of Li-ion battery management systems, this book is an ideal reference for researchers involved in batteries and energy storage. Moreover, the step-by-step guidance and comprehensive introduction to the topic makes it accessible to audiences of all levels, from experienced engineers to graduates. Explains how to model battery systems, including equivalent, electrical circuit and electrochemical nernst modeling Includes comprehensive coverage of battery state estimation methods, including state of charge estimation, energy prediction, power evaluation and health estimation Provides a dedicated chapter on active control strategies

• | Author: Shunli Wang, Carlos Fernandez, Yu Chunmei, Fan Yongcun, Cao Wen, Daniel-Ioan Stroe, Zonghai Chen
• | Publisher: Elsevier
• | Publication Date: June 25, 2021
• | Number of Pages: 354 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 0323904726
• | ISBN-13: 9780323904728