Abstract
The estimation of battery parameters and states at both battery pack and cell levels are studied using the extended Kalman filter (EKF). The estimation results are evaluated with Chevy BOLT electric vehicle data. The cell level estimation when applying EKF is more challenging and an appropriate scaling of cell parameters is required, due to the fact that the current and voltage values of a cell are quite different in magnitude. This estimation study also shows that the cell-level parameter estimation can provide important health information to a battery management system (BMS) for diagnostics and prognostics. The cell-level estimates are then used to predict the voltage limited battery pack power available to a vehicle when a weak cell or droop cell occurs. This power limit can avoid over-discharging a droop cell and protect it from further damage.
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