A new model for State-of-Charge (SOC) estimation for high-power Li-ion batteries
A new model for State-of-Charge (SOC) estimation for high-power Li-ion batteries
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DOI：
10.1016/j.apenergy.2012.08.031
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发表时间：
2013
期刊：
影响因子：
11.2
通讯作者：
Yao He;Xingtao Liu;Chenbin Zhang;Zonghai Chen
中科院分区：
文献类型：
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作者：
Yao He;Xingtao Liu;Chenbin Zhang;Zonghai Chen
荷电状态（SOC）是电动汽车动力电池系统的重要评价指标。为了消除电流传感器漂移噪声的影响，提出了一种以漂移电流为状态变量的高功率锂离子电池工作模型。与此结果相结合，包含温度，充放电率和行驶里程作为变量的总可用容量表达式由实际运行数据重建，以提高模型精度，以应用于电动汽车。为了抑制工作模型的参数摄动，采用无迹粒子滤波（UPF）方法对SOC进行估计，并通过实验和数值仿真验证了工作模型和UPF方法的优越性。结果表明，基于工作模型的UPF方法可以提高SOC估计的精度和鲁棒性。
The State-of-Charge (SOC) is an important evaluation index for power battery systems in electric vehicles. To eliminate the effects of drift noise in the current sensor, a new working model that takes the drift current as a state variable is proposed for high-power Li-ion batteries. In conjunction with this result, a total available capacity expression that involves the temperature, charge–discharge rate, and running mileage as variables is reconstructed by the actual operation data to improve the model accuracy for application to electric vehicles. Then, to suppress the parameter perturbations of the working model, the Unscented Particle Filter (UPF) method is applied to estimate the SOC. Experiments and numerical simulations are conducted to verify the superiority of the working model and the UPF method. The results show that the UPF method based on the working model can improve the accuracy and the robustness of the SOC estimation.