Modeling And State Estimation Of Automotive Lithium-Ion Batteries
Language: English
Published by Taylor & Francis Ltd, 2026
- Softcover
- New
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
AbeBooks seller since January 6, 2003
Condition: New
£ 85.24
Quantity: 2 available
Add to basketItem description from seller
134 pages. 6.14x0.33x9.21 inches. In Stock.
Seller Inventory # x-1032781157
- Title
- Modeling And State Estimation Of Automotive Lithium-Ion Batteries
- Author
- Wang, Shunli Wu, Fan Qiao, Jialu Fernandez, Carlos Guerrero, Josep M
- Publisher
- Taylor & Francis Ltd
- Publication year
- 2026
- Condition
- Brand New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1032781157
- ISBN 13
- 9781032781150
- Item weight
- 0.27 kilograms
This book aims to evaluate and improve the state of charge (SOC) and state of health (SOH) of automotive lithium-ion batteries.
The authors first introduce the basic working principle and dynamic test characteristics of lithium-ion batteries. They present the dynamic transfer model, compare it with the traditional second-order reserve capacity (RC) model, and demonstrate the advantages of the proposed new model. In addition, they propose the chaotic firefly optimization algorithm and demonstrate its effectiveness in improving the accuracy of SOC and SOH estimation through theoretical and experimental analysis.
The book will benefit researchers and engineers in the new energy industry and provide students of science and engineering with some innovative aspects of battery modeling.
"Synopsis" may belong to another edition of this title.
About the Author
Shunli Wang is Professor, Academic Dean, Academic Leader of the National Electrical Safety and Quality Testing Center, Academician of the Russian Academy of Natural Sciences, Senior Overseas Study Talent of Sichuan Province, and Academic and Technical Leader of China Science and Technology City. He is an authoritative expert in renewable energy research and is interested in modeling, state estimation, and safety management for energy storage systems.
Fan Wu is in the School of Information Engineering at Southwest University of Science and Technology. Her research direction is the high-precision state estimation and safety management for energy storage systems. She has published two SCI papers and one international conference paper, authorized a software copyright, and won a national scholarship.
Jialu Qiao is in the School of Information Engineering at Southwest University of Science and Technology. Her research direction is the estimation of the state of charge and health of lithium-ion batteries. She has published three SCI papers as the lead author and one international conference paper, authorized software copyright, and applied for a national invention patent.
Carlos Fernandez is Professor at Robert Gordon University, Head of the MSc in Analytical Sciences Program, and Member of the National Institute of Battery Research. Specializing in analytical chemistry/sensors and materials/renewable energy research, he has led and participated in more than 20 projects with a cumulative economic benefit of £270,000. He has published over 150 papers in SCI-1 and other journals, participated in over 200 reviews, and published three books.
Josep M. Guerrero has been Professor in the Department of Energy Technology at Aalborg University in Denmark since 2011, where he leads the Microgrid research project. In 2019, he became Fluff Fellow at the Villum Fonden, where he is the Founder and Director of the Center for Research on Microgrids (CROM). His research interests are oriented toward different microgrid aspects, including power electronics distributed energy storage systems, hierarchical and cooperative control, energy management systems, smart metering, sustainable energy, and the internet of things for AC/DC microgrid clusters and islanded mini-grids.
"About the title" may belong to another edition of this title.
Revaluation Books
Exeter, United Kingdom
AbeBooks seller since January 6, 2003
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Edward Bowditch Ltd
Exstowe, Exton
Exeter, United Kingdom EX3 0PP
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