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Battery System Modeling

; Carlos Fernandez ; Yu Chunmei ; Fan Yongcun ; Cao Wen ; Daniel-Ioan Stroe ; Zonghai Chen

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. Les mer
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1661,-

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Leveringstid: Sendes innen 7 virkedager

Paperback
Legg i
Paperback
Legg i
Vår pris: 1661,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 7 virkedager

Om boka

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.

Fakta

Innholdsfortegnelse

1. Li-ion Battery Characteristics and Applications 2. Electrical Equivalent Circuit Modeling 3. Electrochemical Nernst Modeling 4. Battery State Estimation Methods 5. Battery State-of-charge Estimation Methods 6. Battery State-of-energy Prediction Methods 7. Battery State-of-power Evaluation Methods 8. Battery State-of-health Estimation Methods 9. Battery System Active Control Strategies

Om forfatteren

Shunli Wang Ph.D is a leading expert on new energy research, DTlab head, New energy measurement & control research team leader. Measurement & control processing is conducted on the needs of the high power Li-ion battery field for its modeling and state estimation strategy. More than 40 projects & 20 patents have been undertaken, publishing over 60 papers on world-famous journals such as Journal of Power Sources, obtaining 20 awards named as Science and Technology Progress Award and University & Enterprise Innovation Talent Team et al. Multiple generation systems have been developed for battery packs, improving the aircraft reliability and expanding its application fields with significant social and economic benefits. Carlos Fernandez MRSC, MECS, MinstP, CChem, Csci, FHEA, PGCert is the Chemistry and Programme Leader in Analytical Sciences at Robert Gordon University with a successful record of bringing over GBP150,000 into the University in research money. Over 80 peer review articles have been published in Physical Chemistry (Electrochemistry) and Materials Chemistry mainly. Expert Evaluator for H2020 Batteries 2019 call (European Commission). Yu Chunmei Ph.D was born in Rugao in Jiangsu Province, being interested in state estimation, system identification, and fault diagnosis. Teaching courses as automatic control theory, system identification, and modeling, etc. for undergraduate and postgraduate students. More than 10 research projects have participated in the recent 5 years, such as the Natural science funding, the Provincial Department of Science and Technology, and projects from enterprises. More than 30 papers have been published on various kinds of worldwide academic journals. Fan Yongcun Ph.D is a core member of the new energy measurement and control research team. Focusing on the measurement and control needs of the new energy field, signal detection and state estimation, anti-interference processing, and control strategy research are carried out to explore the state detection and control theory. Cao Wen Ph.D main research is based on the battery measurement and control technology, the research of charging algorithms, sensors, and the experimental test device is carried out. In the past five years, he has undertaken more than 10 scientific research projects of the Ministry of education of China and the science and Technology Department of Sichuan Province and published more than 20 research papers together with lab members. Daniel-Ioan Stroe Ph.D received the Dipl.-Ing. degree in automatics from the Transylvania University of Brasov, Brasov, Romania, in 2008, and the M.Sc. degree in wind power systems and the Ph.D. degree in lifetime modelling of lithium-ion batteries from Aalborg University, Aalborg, Denmark, in 2010 and 2014, respectively. He is currently an Assistant Professor with the Department of Energy Technology, Aalborg University. He was a Visiting Researcher at RWTH Aachen, Germany, in 2013. He has coauthored more than 70 journals and conference papers. His current research interests include energy storage systems for grid and e-mobility, Lithium-based batteries testing and modelling, and lifetime estimation of lithium-ion batteries. Zonghai Chen Ph.D was born in Anhui, China, in December 1963. He received the B.S. and M.E. degrees from the University of Science and Technology of China (USTC), Hefei, China, in 1988 and 1991, respectively. He has been a Professor with the Department of Automation, USTC, since 1998. His main research interests include modeling and control of complex systems, intelligent robotic and information processing, energy management technologies for electric vehicles, and smart microgrids. Prof. Chen is a recipient of special allowances from the State Council of China. He is a member of the Robotics Technical Committee and Modelling, Identification and Signal Processing Technical Committee of the International Federation of Automation Control.