考虑内阻时变特性的电池状态估计方法

Battery state estimation method with considering internal resistance time-varying characteristics

摘要:

针对锂离子电池欧姆内阻随温度变化情况,提出了一种考虑内阻时变特性的两步无迹H∞滤波锂电池状态估计方法。首先,对锂电池和内阻抗进行分开建模,在电池Thevenin模型的基础上构建内阻抗预测模型,实时修正模型参量；接着,将无迹变换嵌入到扩展H∞滤波中,降低测量噪声对估计精度的扰动,从而提高电池荷电状态的估计精度。最后,在实验室环境下对电池进行充放电实验,分别针对降温和升温情况下的内阻值及电池端电压的估计进行了详细的实验分析,同传统方法相比,本文方法具有较高的估计精度。

Abstract:

In view of the lithium ion battery ohm resistance changes with temperature, this paper proposes a two step unscented h-infinity filtering lithium battery state estimation method with considering internal resistance time-varying characteristics. First of all, the paper models the lithium battery and internal impedance separately, and correct model parameters real-time based on the battery internal resistance prediction model in Thevenin model. Second, the disturbance of measurement noise on estimation accuracy is reduced by the extension of unscented transform into h-infinity filtering framework. The method improves the estimation precision of the battery charged state. Finally, the battery charge and discharge experiments in the laboratory environment show that this method has high estimation precision.