State of health estimation algorithm of LiFePO4 battery packs based on differential voltage curves for battery management system application

Aging datasets of 18 cells with identical chemistry were used for both parametrization and validation. The cells were subjected to a wide range of cycling and storage conditions, including temperature, state of charge, charging and discharging rate, depth of discharge and state of health. The performance and robustness of the estimation are validated by means of the degradation datasets from more than 25 different scenarios at the cell and battery pack level. The related results indicate that the proposed health management strategy has an average relative error of 1.5% at the battery pack level.