Li-Ion batteries have been widely applied in power engineering. Aiming at online state of health (SOH) estimation of Li-Ion batteries, this letter develops a data-driven method using a novel energy-based health indicator (HI). The proposed HI is extracted from the discharge process considering that the discharge process is often less controllable than the charge process. Unlike previous works where only voltage sequences are considered, this HI incorporates both voltage sequences and discharge rates. Therefore, the developed HI enables online SOH estimation at different discharge rates from the offline training dataset. An open dataset is used for verification of the proposed method and very high accuracy is reported with an average RMSE of 1.23%.

中文翻译：

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使用基于能量的新型健康指标在线估计锂离子电池健康的数据驱动方法

锂离子电池在电力工程中得到了广泛的应用。针对锂离子电池的在线健康状态 (SOH) 估计，这封信开发了一种使用新型基于能量的健康指标 (HI) 的数据驱动方法。考虑到放电过程通常不如充电过程可控，建议的 HI 是从放电过程中提取的。与之前只考虑电压序列的工作不同，此 HI 包含电压序列和放电率。因此，开发的 HI 可以从离线训练数据集中以不同的放电率进行在线 SOH 估计。一个开放的数据集用于验证所提出的方法，并且报告了非常高的准确度，平均 RMSE 为 1.23%。