基于自恢复效应电池放电模型及其应用研究

Research on Battery Discharge Model and Application Based on Self- Recovery Effect

现有电池SOC预测方法,大都基于开路电压、开路电流等外电路或者测量电源内阻的方法,而没有考虑到电源的内在特性,尤其没有考虑电池的自恢复效应的影响,且大都采用恒压、恒流放电的工作模式,难以实现对电池SOC的动态预测。针对电池SOC预测方法的缺点,提出了一种包含有电池自恢复效应的电池SOC动态预测方法:提出一款包含有电池自恢复效应的动态电池模型,基于此电池模型提出了计及电池自恢复效应的动态放电模型,并论述了此放电模型与自恢复效应的关系,仿真结果表明,本预测方法具有较高的预测精度,且可实现动态预测。

Most existing battery state of charge（ SOC） prediction methods are based on external circuit measurement such as open circuit voltage and open circuit current or internal resistance measurement of the power. They have not taken into account the inherent characteristics of the power supply,especially the self- recovery effect of the battery.In addition,most of these methods use constant voltage or a constant current discharge mode,which is difficult to achieve dynamic prediction of battery SOC. Considering these disadvantages,the paper presents a dynamic prediction method for battery SOC with self- recovery effect. The dynamic battery model including self- recovery effect is proposed. Based on the model,the dynamic discharge model considering self- recovery effect is proposed,and the relationship between the model and the self- recovery effect is discussed. Simulation results show that the proposed prediction method has higher accuracy,and can achieve dynamic prediction.