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Diagnosis of Internal Short Circuit for Lithium Ion Battery Pack Under Varying Temperature

机译：温度变化对锂离子电池组内部短路的诊断

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摘要

A model based internal short circuit fault diagnosis method for a series-connected battery pack under varying temperature is proposed in this paper. Systematic experiments are conducted to study the relationship between battery capacity, internal resistance and temperature. Internal short circuit fault can be diagnosed based on the decay of dischargeable capacity. To reduce the computational complexity of estimating state of charge(SOC) and diagnosing faults online, a dual time-scale approach is proposed to select standard cell and updating cell. Based on the approach, unscented kalman filter and extended kalman filter are utilized to estimate battery pack SOC. With the accurate SOC, recursive least squares algorithm is utilized to quantitatively diagnose the fault. Finally, dynamic stress test on a series-connected battery pack is conducted to evaluate the proposed method. The results indicate that the method can accurately diagnose the fault in a reasonable time.
机译：提出了一种基于模型的变温串联电池组内部短路故障诊断方法。进行了系统的实验，以研究电池容量，内部电阻和温度之间的关系。可以根据可放电容量的衰减来诊断内部短路故障。为了降低估计荷电状态和在线诊断故障的计算复杂度，提出了一种双时标方法来选择标准单元和更新单元。基于该方法，利用无味卡尔曼滤波器和扩展卡尔曼滤波器来估计电池组SOC。利用准确的SOC，可使用递归最小二乘算法对故障进行定量诊断。最后，在串联电池组上进行了动态应力测试，以评估所提出的方法。结果表明，该方法可以在合理的时间内准确地诊断出故障。

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