A State of Health Estimation Method for Lithium-Ion Batteries Based on Voltage Relaxation Model

Qiaohua Fang, Xuezhe Wei, Tianyi Lu, Haifeng Dai and Jiangong Zhu
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Qiaohua Fang: Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804, China
Xuezhe Wei: Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804, China
Tianyi Lu: Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804, China
Haifeng Dai: Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804, China
Jiangong Zhu: Clean Energy Automotive Engineering Center, Tongji University, Shanghai 201804, China

Energies, 2019, vol. 12, issue 7, 1-18

Abstract: The state of health estimation for lithium-ion battery is a key function of the battery management system. Unlike the traditional state of health estimation methods under dynamic conditions, the relaxation process is studied and utilized to estimate the state of health in this research. A reasonable and accurate voltage relaxation model is established based on the linear relationship between time coefficient and open circuit time for a Li 1 (NiCoAl) 1 O 2 -Li 1 (NiCoMn) 1 O 2 /graphite battery. The accuracy and effectiveness of the model is verified under different states of charge and states of health. Through systematic experiments under different states of charge and states of health, it is found that the model parameters monotonically increase with the aging of the battery. Three different capacity estimation methods are proposed based on the relationship between model parameters and residual capacity, namely the α -based, β -based, and parameter–fusion methods. The validation of the three methods is verified with high accuracy. The results indicate that the capacity estimation error under most of the aging states is less than 1%. The largest error drops from 3% under the α-based method to 1.8% under the parameter–fusion method.

Keywords: voltage relaxation model; capacity estimation; lithium-ion battery; battery management system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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