Grey system theory-based capacity estimation method for Li-ion batteries

The SOC and SoH of Li-ion batteries are of prime importance in EVs and their condition monitoring techniques have been extensively studied. This paper proposes a grey system theory for predicting the battery capacity and healthy conditions in relation to their discharge cycles. Numerical results via grey system theory-based models are obtained based on the aging data from NASA prognostics data repository. Therefore, the accuracy for the SOC estimation can be examined and improved. In this paper, the accuracy of different grey models including GM (1,1), segmental GM (1,1), Verhulst model, sliding window Verhulst model are investigated and the sliding window Verhulst model is found to be effective for EV batteries.