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《Chinese Journal of Power Sources》 2014-05
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SOC estimation based on BP neural network and characteristics of lead-acid battery

ZHAO Xuan;KANG Liu-wang;WANG Gui-ping;MA Jian;School of Automobile, Chang'an University;School of Electric and Control Engineering,Chang'an University;  
The battery characteristics are the key factors determining the charging time and driving range of electric vehicle, and it is of great significance to study on the widely used lead-acid battery. The charging and discharging model of the lead-acid battery was built based on the RC equivalent circuit, and the equation between the model parameters and state-of-charge(SOC) was calculated through variable rates' charging and discharging experiments.The SOC of the lead-acid battery was estimated with BP neural network model, and the simulation study of the lead-acid battery charging and discharging process were carried out based on the SOC neural network model under Matlab circumstances. The simulation results show that the lead-acid battery model could actually simulate charging and discharging characteristics, and the average error between simulation results and test results could reach2.5%.
【Fund】: 陕西省科技计划项目(2010K01-071);; 中央高校基金基础研究项目(2013G1221027);中央高校基金创新团队项目(2013G3322009)
【CateGory Index】: TM912
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