基于电化学机理模型的锂离子电池参数辨识及SOC估计

Lithium-Ion Battery Parameter Identification and SOC Estimation Based on Electrochemical Models

采用Fisher信息矩阵进行参数可辨识性分析,解决了参数的辨识问题,进而提出了基于简化电化学机理模型SP2D(simple pseudo-two-dimensional)的SOC(电池电量)在线估计方法。实验表明,该SOC估计方法较基于等效电路模型(一阶RC模型)的SOC估计方法,可将SOC估计的平均误差减小近30%,而在电池放电中后期更可减小达60%,有效解决了在电池全工作范围内的SOC高精度估计问题。

The Fisher information matrix was adopted to identify the parameters of a lithium-ion battery, and an online SOC(state of charge) estimation method was proposed based on the SP2D (simple pseudotwo- dimensional) model. Compared with the results of the equivalent circuit model, the experiment verifies that the proposed SOC estimation method has higher precision. Effectively solving the problem of SOC high accuracy estimation in the whole range of SOC, the average error of SOC can be reduced by nearly 30%, and by 60% in the later stage of battery discharge.