Data-driven SOH prediction for EV batteries

As electric vehicles (EVs) have been popularized, research on battery management system (BMS) of EVs’ core technology has considerably drawn attention. Among various functions of BMS, predicting state-of-health (SOH) that indexes batteries’ aging is the most crucial to determine replacement time of the battery or to estimate driving mileage. This paper studies how to predict SOH in practical EV environments where the batteries are charged and discharged dynamically.

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