A New Method for State of Charge Estimation of Lithium-Ion Battery Based on Strong Tracking Cubature Kalman Filter
A New Method for State of Charge Estimation of Lithium-Ion Battery Based on Strong Tracking Cubature Kalman Filter
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DOI：
10.3390/en81212378
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发表时间：
2015-11
期刊：
影响因子：
3.2
通讯作者：
Bizhong Xia;Haiqing Wang;Mingwang Wang;Wei Sun;Zhihui Xu;Yongzhi Lai
中科院分区：
文献类型：
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作者：
Bizhong Xia;Haiqing Wang;Mingwang Wang;Wei Sun;Zhihui Xu;Yongzhi Lai
荷电状态（SOC）的估计是电池管理系统（BMS）中的一个重要评价指标。SOC的值表示电池的剩余容量，它为电池运行的安全性和可靠性提供了很好的保证。SOC作为一种内部状态，很难得到准确的值。本文在容积卡尔曼滤波器的基础上，提出了一种强跟踪容积卡尔曼滤波器（STCKF），以实现准确可靠的SOC估计。STCKF算法通过在状态估计协方差矩阵中引入衰落因子，在线调整增益矩阵。采用典型的二阶阻容模型作为电池的等效电路模型，对电池的特性进行动态仿真。指数函数拟合法完成了相关参数的辨识任务。在此基础上，对STCKF算法进行了详细的介绍，并在动态应力测试（DST）和新欧洲行驶工况（NEDC）等不同工况下进行了验证。通过与扩展卡尔曼滤波器（EKF）和CKF算法的比较，实验结果表明STCKF算法在SOC估计精度和鲁棒性方面的优势。
The estimation of state of charge (SOC) is a crucial evaluation index in a battery management system (BMS). The value of SOC indicates the remaining capacity of a battery, which provides a good guarantee of safety and reliability of battery operation. It is difficult to get an accurate value of the SOC, being one of the inner states. In this paper, a strong tracking cubature Kalman filter (STCKF) based on the cubature Kalman filter is presented to perform accurate and reliable SOC estimation. The STCKF algorithm can adjust gain matrix online by introducing fading factor to the state estimation covariance matrix. The typical second-order resistor-capacitor model is used as the battery’s equivalent circuit model to dynamically simulate characteristics of the battery. The exponential-function fitting method accomplishes the task of relevant parameters identification. Then, the developed STCKF algorithm has been introduced in detail and verified under different operation current profiles such as Dynamic Stress Test (DST) and New European Driving Cycle (NEDC). Making a comparison with extended Kalman filter (EKF) and CKF algorithm, the experimental results show the merits of the STCKF algorithm in SOC estimation accuracy and robustness.