铅酸蓄电池模型研究及SOC模糊估计

为了深入研究铅酸蓄电池在充放电过程中内阻等特征参数的变化,首先,基于铅酸蓄电池的工作机理建立蓄电池充放电模型,并进行不同倍率的充放电实验;其次,基于实验数据建立各模型参数与SOC之间的函数关系,同时对BP神经网络模型进行训练以实现SOC的精确估计。最后,结合铅酸蓄电池充放电模型和BP神经网络模型仿真铅酸蓄电池充放电过程,仿真结果和实际结果吻合,有助于对铅酸蓄电池内阻等特征参数的研究。

Study on the model of lead-acid battery and fuzzy estimation of state-of-charge

To further study the battery characteristic parameters such as the internal resistance during the charging and discharging process, the paper firstly built the lead-acid battery model based on the work mechanism and carried on the charging and discharging experiments at different current rates. And then, based on the experiments data, the functions between the model parameters and the SOC were established and the BP neural network model was trained to estimate the SOC. Finally, the battery model was combined with the neural network model to simulate the lead-acid battery charging and discharging process. The simulation showed that the simulations could better describe the battery work mechanism and help to study the characteristic parameters.