馬達智財聯盟 Motor Intellectual Property Alliance

作者	Benvolence Chinomona , Chunhui Chung , Lien-Kai Chang , Wei-Chih Su and Mi- Ching Tsai
摘要	Due to the increase of electrical vehicles (EVs) demands, prognostics of the battery state is of paramount important. This study proposes a feature selection technique to adequately select optimum statistical feature subset and use of partial discharge data using National Aeronautics and Space Administration battery data set. The proposed approach demonstrated exceptional remaining useful life (RUL) prediction using partial data compared to full discharge data.
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