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Long-term health state estimation of energy storage lithium-ion battery packs

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Long-term health state estimation of energy storage lithium-ion battery packs/ by Qi Huang ... [et al.].
其他作者:	Huang, Qi.
出版者:	Singapore :Springer Nature Singapore : : 2023.,
面頁冊數:	xi, 92 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Mathematical Modeling and Industrial Mathematics. -
電子資源:	https://doi.org/10.1007/978-981-99-5344-8
ISBN:	9789819953448

Long-term health state estimation of energy storage lithium-ion battery packs
Long-term health state estimation of energy storage lithium-ion battery packs[electronic resource] /by Qi Huang ... [et al.]. - Singapore :Springer Nature Singapore :2023. - xi, 92 p. :ill. (some col.), digital ;24 cm.

Chapter 1 Introduction -- Chapter 2 Electrochemical modeling of energy storage lithium battery -- Chapter 3 Extraction of multidimensional health indicators based on lithium-ion batteries -- Chapter 4 Research on health state estimation method of the lithium-ion battery pack -- Chapter 5 Experimental verification and analysis of health state estimation for lithium-ion battery pack.

This book investigates in detail long-term health state estimation technology of energy storage systems, assessing its potential use to replace common filtering methods that constructs by equivalent circuit model with a data-driven method combined with electrochemical modeling, which can reflect the battery internal characteristics, the battery degradation modes, and the battery pack health state. Studies on long-term health state estimation have attracted engineers and scientists from various disciplines, such as electrical engineering, materials, automation, energy, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of extraction for health indicators and the significant influence of electrochemical modeling and data-driven issues in the design and optimization of health state estimation in energy storage systems. The book is intended for undergraduate and graduate students who are interested in new energy measurement and control technology, researchers investigating energy storage systems, and structure/circuit design engineers working on energy storage cell and pack.

ISBN: 9789819953448

Standard No.: 10.1007/978-981-99-5344-8doiSubjects--Topical Terms:

669172
Mathematical Modeling and Industrial Mathematics.

LC Class. No.: TK2945.L58

Dewey Class. No.: 621.312424

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520 $a This book investigates in detail long-term health state estimation technology of energy storage systems, assessing its potential use to replace common filtering methods that constructs by equivalent circuit model with a data-driven method combined with electrochemical modeling, which can reflect the battery internal characteristics, the battery degradation modes, and the battery pack health state. Studies on long-term health state estimation have attracted engineers and scientists from various disciplines, such as electrical engineering, materials, automation, energy, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of extraction for health indicators and the significant influence of electrochemical modeling and data-driven issues in the design and optimization of health state estimation in energy storage systems. The book is intended for undergraduate and graduate students who are interested in new energy measurement and control technology, researchers investigating energy storage systems, and structure/circuit design engineers working on energy storage cell and pack.
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