A Training-Free Estimation Method for the State of Charge and State of Health of Series Battery Packs under Various Load Profiles

Lei Pei, Cheng Yu, Tiansi Wang (), Jiawei Yang and Wanlin Wang
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Lei Pei: Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
Cheng Yu: Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
Tiansi Wang: School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Jiawei Yang: Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
Wanlin Wang: Farasis Energy (ZhenJiang) Co., Ltd., Zhenjiang 212132, China

Energies, 2024, vol. 17, issue 8, 1-20

Abstract: To ensure the accuracy of state of charge (SOC) and state of health (SOH) estimation for battery packs while minimizing the amount of pre-experiments required for aging modeling and the scales of computation for online management, a decisive-cell-based estimation method with training-free characteristic parameters and a dynamic-weighted estimation strategy is proposed in this paper. Firstly, to reduce the computational complexity, the state estimation of battery packs is summed up to that of two decisive cells, and a new selection approach for the decisive cells is adopted based on the detection of steep voltage changes. Secondly, two novel ideas are implemented for the state estimation of the selected cells. On the one hand, a set of characteristic parameters that only exhibit local curve shrinkage with aging is chosen, which keeps the corresponding estimation approaches away from training. On the other hand, multiple basic estimation approaches are effectively combined by their respective dynamic weights, which ensures the estimation can maintain a good estimation accuracy under various load profiles. Finally, the experimental results show that the new method can quickly correct the initial setting deviations and have a high estimation accuracy for both the SOC and SOH within 2% for a series battery pack consisting of cells with obvious inconsistency.

Keywords: series battery pack; SOC and SOH; selection of decisive cells; training-free estimation; dynamic weight distribution (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: 2024
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