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27 November 2019 A research on cell inconsistency prediction of power battery using Gaussian process regression
Liu Ling, Song Chao, Yong-bo Xie, Wen-ming Wang, Xiong Gang, Li Xi
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Proceedings Volume 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence; 1132120 (2019) https://doi.org/10.1117/12.2542386
Event: The Second International Conference on Image, Video Processing and Artifical Intelligence, 2019, Shanghai, China
Abstract
Cell inconsistency affect battery life and driving safety. In order to solve the accuracy problem of online prediction of cell inconsistency of power battery, battery characteristic analysis based on of vehicle network big data is proceeded, health indicator(HI), based on the cell terminal voltage difference,is proposed through the degradation model; As the similar distribution of cell terminal voltage difference between battery discharge conditions, the health indicator sequence based on SOC(State of Charge) is constructed, and the next health indicator is predicted by Gaussian process regression. The prediction results show that the method requires less training samples and less hardware resources, and the overall prediction accuracy is not less than 85%, which can meet the practical requirements.
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Liu Ling, Song Chao, Yong-bo Xie, Wen-ming Wang, Xiong Gang, and Li Xi "A research on cell inconsistency prediction of power battery using Gaussian process regression", Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 1132120 (27 November 2019); https://doi.org/10.1117/12.2542386
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KEYWORDS
Data modeling
Statistical modeling
Resistance
Safety
Algorithm development
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