期刊
出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.egypro.2016.06.088
关键词
battery model; parameter adaptive battery model; sliding mode observer; SOC estimation
Errors of a battery model will dramatically enlarge as the internal parameters of a battery varying. To reduce the systematic errors, a parameter adaptive battery model is proposed. Based on it, sliding mode algorithm is adopted to estimate the SOC of a battery. The experimental platform is constructed and the UDDS driving cycles is used to verify the method. The results show the error of SOC estimation is less than 2% and it indicates the monitoring algorithm is of great value to power batteries which are generally used in variable environment. (C) 2016 The Authors. Published by Elsevier Ltd.
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