Capacity estimation for lithium-ion battery using experimental feature interval approach

Pucheng Pei, Qibin Zhou, Lei Wu, Ziyao Wu, Jianfeng Hua and Huimin Fan

Energy, 2020, vol. 203, issue C

Abstract: The estimation of lithium-ion battery capacity is of great importance in electric vehicle battery management system (BMS), its results will contribute to controlling the battery to have both excellent output performance and long life. However, there still lacks generalized approaches for different kinds of batteries with high estimating accuracy. Therefore, an experimental feature interval approach for LiFePO4 (LFP) and LiNixCoyMn1-x-yO2 (NCM) capacity estimating is proposed in this paper. Firstly, two concepts of feature interval and remaining charge electricity (RCE) are defined, then partial charging electricity based on incremental capacity analysis is used to estimate capacity. According to the results, there is a strong linear relationship between RCE and capacity. We can obtain capacity directly through this linear function by calculating RCE from the feature interval to the end of charge. A satisfying estimation performance is verified by the results of another experiment data, where the accuracy is more than 98.5%. Moreover, it is found that this approach can be used to NCM battery by modifying the linear fitting weights. This proposed approach is verified in NASA dataset, with the estimating deviations less than 2.4%. Further, the proposed estimating approach may serve as a reference for batteries from other manufactures.

Keywords: Lithium-ion battery; Capacity estimation; Battery management system; Incremental capacity analysis (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:203:y:2020:i:c:s0360544220308859

DOI: 10.1016/j.energy.2020.117778

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