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

• Published in: Energy (Oxford) Vol. 203; p. 117778
• Main Authors: Pei, Pucheng, Zhou, Qibin, Wu, Lei, Wu, Ziyao, Hua, Jianfeng, Fan, Huimin
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 15-07-2020; Elsevier BV
• Subjects: Batteries; Battery management system; Capacity estimation; Electric vehicles; Electricity; Estimation; Incremental capacity analysis; Linear functions; Lithium; Lithium-ion batteries; Lithium-ion battery; Rechargeable batteries; Incremental capacity analysis; Lithium-ion battery; Battery management system; Capacity estimation
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2020.117778

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.
•Concepts of feature interval and remaining-charge-electricity are proposed.•Remaining-charge-electricity exhibits a strong linear relation with capacity.•The experimental results show the deviations of estimation are less than 2.5%.