State-of-Charge estimation for power Li-ion battery pack using V min -EKF
State-of-Charge estimation for power Li-ion battery pack using V min -EKF
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发表时间：
2010-06
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通讯作者：
Xintian Liu;Yao He;Zonghai Chen
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作者：
Xintian Liu;Yao He;Zonghai Chen
动力电池组荷电状态（SOC）的准确估计在电动汽车的应用中非常重要。单节电池型号不适用于 m u Iti 电池组的电池组。考虑串联电池组的不平衡特性，提出V mi1i模型。电池组的最小电池负载电压(V mi1i )被用作模型测量变量，SOC被用作模型状态变量。基于V min 状态空间模型，应用扩展凯曼滤波器（EFK）方法来递归估计电池组的SOC。进行了实验来模拟电池组在驾驶条件下的行为。结果表明，通过该方法可以获得准确、实时的SOC估计。
An accurate estimation of State-of-Charge (SOC) for power battery pack is very important in the applications of electrical vehicles. Single cell model is not suitable for battery pack of m u Iti cells. Considering the imbalance characteristic of serial connected battery pack, a V mi1i model is proposed. The minimal cell load voltage of the battery pack (V mi1i ) is used as the model measurement variable, and SOC is used as the model state variable. Based on the V min state space model, the extended Kaiman filter (EFK) approach is applied to get the recursive estimation of the battery pack's SOC. Experiments were made to simulate the behaviors of battery pack in the driving conditions. The results showed that accurate and real-time estimation of SOC could be obtained through this approach.