锂(药物)
电压
离子
区间(图论)
估计
材料科学
数学
化学
电气工程
工程类
医学
内科学
组合数学
有机化学
系统工程
作者
Teng Wang,Yuhao Zhu,Zhen Zhang,Feng Bi,Luoran Sun,T O Kim,Yunlong Shang
标识
DOI:10.1109/tte.2025.3556447
摘要
It is of great significance to scientifically and conveniently characterize the state of health (SOH) for lithium-ion batteries (LIBs). However, due to the inherent complex reaction mechanism, the high nonlinearity and strong time variation of battery degradation are increasingly prominent. The traditional SOH estimation methods require complete chargedischarge information, which are difficult to obtain in practical applications. How to obtain SOH accurately and conveniently under actual conditions is a key and challenging problem. Hence, an SOH estimation method based on incremental capacity analysis (ICAs) is proposed, which divides the charging voltage into several microintervals. The optimal interval is obtained according to the peak distribution of incremental capacity (IC) curve. SOH is calculated by the charging capacity within the optimal microvoltage interval. The accuracy and effectiveness are verified with multiple datasets, which are produced by four different manufactures. Experimental results show that the mean error of calculated SOH is 0.7% under different datasets. The 79.25% time can be saved compared with traditional method, which also brings the superior robustness, high practicability, and strong generalization. More importantly, the proposed method is promising for SOH rapid acquisition under various applications, such as electric vehicles (EVs) and energy storage services.
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