基于经验方程的蓄电池荷电状态辨识模型的改进

Improvement to the Battery SOC Identification Models on Experiential Equation

为了提高基于经验方程的蓄电池荷电状态辨识模型的辨识精度,提出了一种对模型方程中端电压补偿因子和内阻补偿因子加以改进的方法;该改进方法是根据噪声信号对蓄电池端电压和内阻的影响,将补偿因子由梯度项改为平方根项;同时利用LabVIEW软件设计出一套仿真分析程序,对改进后的模型进行仿真分析及验证;结果表明,改进后的辨识模型可以有效地减小噪声干扰给辨识结果造成的误差,辨识精度较高。

In order to improve the precision of the battery SOC identification models on experiential equation, this paper introduces an improvement to the terminal voltage compensate factor and internal resistance compensate factor of the models equation. Because the signals of terminal voltage and internal resistance have much noise, we replace the compensate factor from gradient to square root. Then a LabVIEW project is designed to prove the correctness of the improved identification models. The result shows that the improved identifieation models can reduce effectively the error caused by noise and it has a high identification accuracy.