SOC在线估计误差修正算法研究

Research on error correction algorithm of SOC online estimation

针对荷电状态(SOC)在线估计精度不高的问题,以磷酸铁锂(Li Fe PO4)锂离子电池为对象,研究环境温度、循环次数和放电电流等因素对电池容量的影响。提出一种误差修正方法,利用开路电压结合BP神经网络估计初始SOC,利用安时积分估计动态SOC。这种方法将SOC的估计精度控制在2%以内,可用于电池管理系统中在线估计SOC。

According to the problem of low precision in state of charge （ SOC ） estimation, the influence of ambient temperature, cycle numbers and discharge current on the capacity of the lithium iron phosphate （ LiFePO4 ） Li-ion battery was studied. A error correction algorithm for SOC estimation was proposed, which was estimate the initial SOC by the combination of open circuit voltage and BP neural network and the dynamics of SOC by Ampere-hour integral. This method could control the precise of SOC estimation within 2% and this algorithm could be applied to battery management system for SOC online estimation.