电池(电)
荷电状态
计算机科学
电压
功率(物理)
汽车工程
电气工程
工程类
物理
量子力学
作者
Mingfang Liu,Feng Rao,Bei Li,Xinya Jiang,Xianggang Meng
出处
期刊:International Journal of Modern Physics B
[World Scientific]
日期:2019-12-30
卷期号:34 (01n03): 2040023-2040023
被引量:2
标识
DOI:10.1142/s0217979220400238
摘要
The key to battery management systems (BMS) is an accurate and real-time prediction on State of Charge (SOC) of the power battery. The methods of estimating SOC of power battery were analyzed. The gray neural network model was introduced into the field of SOC estimation. The model is used to establish the relationship of SOC, discharge current and rebound voltage. The model can be used to estimate SOC of battery on line by detecting the values of rebound voltage and discharge current during the discharge process. The model of SOC estimation is proved feasible by comparing the experimental data with calculated data.
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