State Estimation Strategies in Lithium-ion Battery Management Systems

State Estimation Strategies in Lithium-ion Battery Management Systems presents key technologies and methodologies in modeling and monitoring charge, energy, power and health of lithium-ion batteries. Sections introduce core state parameters of the lithium-ion battery, reviewing existing research and the significance of the prediction of core state parameters of the lithium-ion battery and analyzing the advantages and disadvantages of prediction methods of core state parameters. Characteristic analysis and aging characteristics are then discussed. Subsequent chapters elaborate, in detail, on modeling and parameter identification methods and advanced estimation techniques in different application scenarios. Offering a systematic approach supported by examples, process diagrams, flowcharts, algorithms, and other visual elements, this book is of interest to researchers, advanced students and scientists in energy storage, control, automation, electrical engineering, power systems, materials science and chemical engineering, as well as to engineers, R&D professionals, and other industry personnel.

General

Imprint:	Elsevier - Health Sciences Division
Country of origin:	United States
Release date:	July 2023
First published:	2023
Authors:	Shunli Wang • Kailong Liu • Yujie Wang • Daniel-Ioan Stroe • Carlos Fernandez • Josep M. Guerrero
Dimensions:	229 x 152mm (L x W)
Pages:	376
ISBN-13:	978-0-443-16160-5
Categories:	Books
LSN:	0-443-16160-7
Barcode:	9780443161605

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