基于神经网络的动力电池SOC研究

Research on estimation for SOC of dynamics battery based on neural network

利用神经网络进行了动力电池荷电状态(SOC)预测研究。在分析磷酸铁锂电池充放电机理的基础上,采用levenberg-marquardt(LM)算法建立了动力电池的BP(back propagation)神经网络模型,并进行了电池SOC值的预测。结果表明,基于神经网络的电池SOC预测方法具有较高的精度,可用来预测磷酸铁锂电池的SOC值。

The state of charge （SOC） of dynamics battery for electric vehicle was estimated by neural network. Based on the electrochemical mechanism of dynamics batteries during charge and discharge, a back propagation （BP） neural network model was built up using Levenberg-Marquardt （LM）. The neural network model was used to estimate SOC of dynamics battery. The results show that the neural network method is a quite accurate algorithm and can be used in estimation of SOC of dynamics batteries.