荷电状态
恒流
电池(电)
电压
健康状况
水准点(测量)
曲线拟合
控制理论(社会学)
电气工程
数学
工程类
计算机科学
物理
功率(物理)
统计
人工智能
控制(管理)
大地测量学
量子力学
地理
作者
Chi-Jyun Ko,Kuo-Ching Chen,Ting-Wei Su
出处
期刊:Energy
[Elsevier]
日期:2024-02-01
卷期号:288: 129826-129826
被引量:6
标识
DOI:10.1016/j.energy.2023.129826
摘要
Compared with extensive discussions on constant current (CC) charging for lithium-ion batteries, the probe into constant voltage (CV) charging is currently insufficient. Analogous to the differential analysis of the voltage curve in CC charging, this paper introduces the differential current curve (dQ/dI curve) in CV charging and uses it as the feature to identify battery states. The differential curve is qualitatively interpreted with an equivalent circuit model, and the relationship between the dQ/dI value and the battery states is fitted with the Gaussian process regression (GPR) model. With a total of 4836 sets of CV charging data, an excellent state of health (SOH) estimation with a mean absolute error (MAE) of 0.18 % can be achieved by using the first 190 data points of the dQ/dI curve as the model input. For state of charge (SOC) estimation, a brand-new experimental work is introduced by adjusting the cutoff voltage of the previous CC charging to generate a benchmark database illustrating the relation between the SOC value at the initial CV charging and the subsequent current curve. Through GPR, the SOC prediction MAE is reduced to about 0.88 %, which confirms that the dQ/dI curve is a promising candidate for battery state estimation.
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