期刊
IECON 2020: THE 46TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY
卷 -, 期 -, 页码 1911-1916出版社
IEEE
DOI: 10.1109/iecon43393.2020.9254332
关键词
Electric vehicles; adaptive dual extended Kalman filter; remaining discharge capacity; state of charge
类别
资金
- Postgraduate Research and Practice Innovation Program of Jiangsu Province [SJKY19_0323, SJCX19_0114]
Battery remaining discharge capacity estimation is of significant importance for Electric Vehicles(EVs) and Battery Energy Storage Systems(BESSs) to obtain the remaining driving distance and remaining energy to be discharged. However, the discharge process terminates when discharge cut-off voltage is reached, and the remaining discharge capacity with different load current rates is difficult to obtain. In this paper, the remaining discharge capacity is defined to describe how much capacity can be discharged when discharge cut-off voltage is reached. It takes State of Charge (SOC), discharge capacity of the whole process and maximum discharge capacity, which takes discharge capacity at 0.05C as a reference, into consideration. A discharge capacity estimation method under constant current and working conditions is verified using an equivalent circuit model. Besides, the SOC is estimated using adaptive dual extended Kalman filter (ADEKF). Experimental results demonstrate that the estimation error of remaining discharge capacity is 0.0074Ah (0.336%).
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