Online cell SOC estimation of Li-ion battery packs using a dual time-scale Kalman filtering for EV applications
Online cell SOC estimation of Li-ion battery packs using a dual time-scale Kalman filtering for EV applications
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DOI：
10.1016/j.apenergy.2012.02.044
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发表时间：
2012-07
期刊：
影响因子：
11.2
通讯作者：
Haifeng Dai;Xuezhe Wei;Zechang Sun;Jiayuan Wang;Weijun Gu
中科院分区：
文献类型：
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作者：
Haifeng Dai;Xuezhe Wei;Zechang Sun;Jiayuan Wang;Weijun Gu
对于车辆操作，由于电压和功率/能量要求，电池系统通常由多达数百个串联或并联连接的电池组成。为了适应运行条件，电池管理系统（BMS）应该估计荷电状态（SOC），以促进电池的安全和有效利用。电池组中电池性能的差异使得单纯的电池组SOC估计难以提供足够的信息，从而影响电池组可用能量和可用功率的计算以及电池系统的安全性。因此，为了进行可靠和准确的管理，BMS应该“知道”每个单独电池的SOC。近年来，报告了关于这一问题的几种可能的解决办法。研究了一种在线确定串联电池组中各单体电池SOC的方法。该方法利用基于等效电路的“平均电池”模型，首先估计电池组的平均SOC，然后结合“平均电池”和每个单独电池之间的性能差异以生成所有电池的SOC估计。该方法基于扩展卡尔曼滤波器（EKF），为了减少计算量，设计了一种双时标实现。利用锂离子电池组在三种不同测试下的测量结果对该方法进行了验证，分析表明该算法具有良好的性能。
For the vehicular operation, due to the voltage and power/energy requirements, the battery systems are usually composed of up to hundreds of cells connected in series or parallel. To accommodate the operation conditions, the battery management system (BMS) should estimate State of Charge (SOC) to facilitate safe and efficient utilization of the battery. The performance difference among the cells makes a pure pack SOC estimation hardly provide sufficient information, which at last affects the computation of available energy and power and the safety of the battery system. So for a reliable and accurate management, the BMS should “know” the SOC of each individual cell. Several possible solutions on this issue have been reported in the recent years. This paper studies a method to determine online all individual cell SOCs of a series-connected battery pack. This method, with an equivalent circuit based “averaged cell” model, estimates the battery pack’s average SOC first, and then incorporates the performance divergences between the “averaged cell” and each individual cell to generate the SOC estimations for all cells. This method is developed based on extended Kalman filter (EKF), and to reduce the computation cost, a dual time-scale implementation is designed. The method is validated using results obtained from the measurements of a Li-ion battery pack under three different tests, and analysis indicates the good performance of the algorithm.