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Joint Grey Correlation Degree based Incremental Capacity Analysis for State-of-Health Estimation of Lithium Ion Battery

机译:基于联合灰色关联度的增量容量分析,用于锂离子电池的健康状态估算

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In order to prolong the service life, increase the efficiency of operation, and ensure the working safety during the usage of lithium ion batteries (LIBs), it is necessary to develop a reliable and accurate state-of-health (SOH) estimation for LIBs. In this context, a novel method based on joint grey relation analysis is proposed to analyze the unique shape of incremental capacity (IC) curve for LIBs. The proposed method obtains optimal partial IC curve according to inverse accumulated generating operation and slope correlation degree. Experiments are conducted on two lithium cobalt batteries for their whole service life to verify the performance of the proposed method. Results show that the proposed method can accurately estimate the SOH with the maximum estimation error of 2.94%.
机译:为了延长使用寿命,提高运行效率并确保锂离子电池(LIB)使用期间的工作安全性,有必要针对LIB制定可靠而准确的健康状态(SOH)估算。在此背景下,提出了一种基于联合灰色关联分析的新型方法来分析LIB的增量容量(IC)曲线的独特形状。所提出的方法根据逆累积生成操作和斜率相关度来获得最优的局部IC曲线。在两个锂钴电池的整个使用寿命上进行了实验,以验证所提出方法的性能。结果表明,该方法可以准确估计SOH,最大估计误差为2.94%。

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