Comparative Study of Incremental Capacity Curve Determination Methods for Lithium-Ion Batteries Considering the Real-World Situation

稳健性(进化) 计算机科学 曲线拟合 算法 控制理论(社会学) 人工智能 机器学习 生物化学 基因 化学 控制(管理)
作者
Peng Liu,Yizhong Wu,Chengqi She,Zhenpo Wang,Zhaosheng Zhang
出处
期刊:IEEE Transactions on Power Electronics [Institute of Electrical and Electronics Engineers]
卷期号:37 (10): 12563-12576 被引量:24
标识
DOI:10.1109/tpel.2022.3173464
摘要

The incremental capacity analysis (ICA) method is a promising method in battery state of health (SOH) estimation studies. The incremental capacity (IC) curve determination is one of the critical parts of the ICA method. However, the uncertain and incomplete charging conditions of real-world electric vehicles (EVs) significantly limit the IC curve determination. This article provides a thorough analysis of the practicality and limitations of four IC curve determination methods based on the datasets collected from real-world operating EVs with a comprehensive comparison scheme. The Lorentz function fitting method is improved by the differential evolution algorithm, breaking the limitation of fixed parameter boundary constraints. A novel PCHIP method is further proposed to determine the IC curve, with higher robustness to realistic uncertain and incomplete charging conditions. The proposed method is validated by real-world data from 40 EVs with low sampling frequency. The results show the extracted features from the IC curves, determined by the proposed method have a stronger correlation with the SOH, allowing the accurate SOH estimation with a 2% error. With less computational resources and sampling frequency requirements, this method shows great potential for the realistic battery management system implementation.
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