电压
电池(电)
开路电压
鉴定(生物学)
荷电状态
转化(遗传学)
控制理论(社会学)
功率(物理)
振幅
电子工程
工程类
计算机科学
电气工程
物理
化学
人工智能
生物化学
植物
控制(管理)
量子力学
基因
生物
作者
Lin Peng,Peng Jin,Hongyin Zhang
出处
期刊:Journal of The Electrochemical Society
[The Electrochemical Society]
日期:2023-03-01
卷期号:170 (3): 030525-030525
被引量:2
标识
DOI:10.1149/1945-7111/acc2ec
摘要
Accurate measurement of the open-circuit voltage (OCV) promotes state of charge (SOC) accuracy. In this study, three transformation methods are employed to make the OCV identifiable, and factors affecting the accuracy of OCV identification are investigated. Furthermore, a fast OCV measurement method is proposed. The results show that the forward difference transformation and the adaptive differential evolution algorithm are more suitable for OCV identification. The accuracy of OCV identification is affected by pulse characteristics, sampling frequency, C-rate, and resting time between pulses. Positive-negative (PN) pulses of equal amplitude are more suitable for OCV identification than hybrid pulse power characteristics. A method for fast OCV measurement is developed based on the relationship between the identification error of the OCV and the number of PN pulses. A total of 57 PN pulses with an amplitude of 2 C are used to realize accurate OCV identification at various charge/discharge states, C-rate, and SOC, with an average error of −0.03% (about 1 mV). The proposed method only needs to obtain the battery voltage and current to achieve a fast measurement of OCV, which also serves as a foundation for an accurate estimation of the battery state.
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