Accurate parameter identification of a lithium-ion battery is a critical basis in the battery management systems. Based on the analysis of the second-order RC equivalent circuit model, the parameter identification process using the recursive least squares (RLS) algorithm is discussed firstly. The reason for the RLS algorithm affecting the accuracy and rapidity of model parameter identification is pointed out. And an improved RLS algorithm is proposed, an inner loop with the estimated parameter vector updated multiple times is inserted into the conventional RLS algorithm, so that the identification results are improved. The test platform of a single lithium-ion battery is built. The experimental results show that the improved RLS algorithm has better tracking ability, smaller prediction error and has a moderate computational burden compared with the conventional RLS algorithm and a variable forgetting factor RLS algorithm.

中文翻译：

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基于改进递推最小二乘算法的锂离子电池参数辨识

锂离子电池的准确参数识别是电池管理系统中的关键基础。基于二阶分析钢筋混凝土在等效电路模型中，首先讨论了采用递归最小二乘（RLS）算法进行参数识别的过程。指出了RLS算法影响模型参数识别精度和速度的原因。提出了一种改进的RLS算法，将估计参数向量多次更新的内环插入到常规的RLS算法中，从而提高了识别效果。构建了单个锂离子电池的测试平台。实验结果表明，与常规RLS算法和遗忘因子RLS算法相比，改进的RLS算法具有更好的跟踪能力，较小的预测误差和适度的计算量。