State Estimation Strategies in Lithium-ion Battery Management Systems

di Shunli Wang (Autore)

Kailong Liu (Autore)

Yujie Wang (Autore)

Elsevier - Health Sciences Division, 2023

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.

• Autore: Shunli Wang, Kailong Liu, Yujie Wang
• Editore: Elsevier - Health Sciences Division
• Anno: 2023
• Rilegatura: Paperback / softback
• Pagine: 376 p.
• Dimensioni: 229 x 152 mm
• Peso: 590 gr.
• EAN: 9780443161605

Testo in English