State of Health Estimation for Lithium-Ion Batteries in Real-World Electric Vehicles
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影响因子：4.7
DOI码：10.1007/s11431-022-2220-y
发表刊物：SCIENCE CHINA Technological Sciences
关键字：lithium-ion battery; electric vehicle; state of health; extreme gradient boosting
摘要：The state of health (SOH) plays a significant role in the mileage and safety of an electric vehicle (EV). In recent years, many methods based on data-driven analysis and laboratory measurements have been developed for SOH estimation. However, most of these proposed methods cannot be applied to real-world EVs. Here, we present a method for SOH estimation based on real-world EV data. A battery-aging evaluation health index (HI) with a strong correlation to the SOH is retrieved from battery-aging data and then modified with thermal factors to depict the former SOH. Afterward, a local weighted linear-regression algorithm is used to qualitatively characterize the declining trend of the HI, which eliminates the local HI fluctuation caused by data noise. Subsequently, a series of features-of-interest (FOIs) is extracted according to the battery consistency, cell-voltage extrema, and cumulative mileage, and validated using the grey relational analysis. Finally, a battery-degradation model is built using the extreme gradient-boosting algorithm with the selected FOIs. The experimental results from real-world data indicate that the proposed method has high estimation accuracy and generalization, and the maximum error is around 2 % for batteries in real-world EVs.
论文类型：期刊论文
学科门类：工学
文献类型：J
卷号：66
期号：1
页面范围：46-56
是否译文：否
发表时间：2023-01-01
收录刊物：SCI
发布期刊链接：https://www.sciengine.com/SCTS/doi/10.1007/s11431-022-2220-y