Review of State Estimation and Remaining Useful Life Prediction Methods for Lithium–Ion Batteries

Jiahui Zhao, Yong Zhu (), Bin Zhang, Mingyi Liu, Jianxing Wang, Chenghao Liu and Xiaowei Hao
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Jiahui Zhao: China Huaneng Group, Clean Energy Research Institute (CERI), Beijing 102209, China
Yong Zhu: China Huaneng Group, Clean Energy Research Institute (CERI), Beijing 102209, China
Bin Zhang: China Huaneng Group, Clean Energy Research Institute (CERI), Beijing 102209, China
Mingyi Liu: China Huaneng Group, Clean Energy Research Institute (CERI), Beijing 102209, China
Jianxing Wang: China Huaneng Group, Clean Energy Research Institute (CERI), Beijing 102209, China
Chenghao Liu: China Huaneng Group, Clean Energy Research Institute (CERI), Beijing 102209, China
Xiaowei Hao: China Huaneng Group, Clean Energy Research Institute (CERI), Beijing 102209, China

Sustainability, 2023, vol. 15, issue 6, 1-22

Abstract: The accurate estimation of the state of charge, the state of health and the prediction of remaining useful life of lithium–ion batteries is an important component of battery management. It is of great significance to prolong battery life and ensure the reliability of the battery system. Many researchers have completed a large amount of work on battery state evaluation and RUL prediction methods and proposed a variety of methods. This paper first introduces the definition of the SOC, the SOH and the existing estimation methods. Then, the definition of RUL is introduced, and the main methods are classified and compared. Finally, the challenges of lithium–ion battery state estimation and RUL prediction are summarized, and the direction for future development is proposed.

Keywords: lithium–ion battery; SOC estimation; SOH estimation; RUL prediction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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