Online Health Estimation of Batteries with Moderate to High Degradation Utilizing LSTM-Ensembled Learning Framework from Consecutive CC Charging Segments
Accurate online state of health (SoH) estimation, especially for highly degraded second-life batteries (SLBs), is critical for the safe and efficient operation of any Battery Management System (BMS). However, existing data-driven estimation methods typically rely on complete charge/discharge cycles or assume a fixed st...