Battery Degradation Prediction Using Incremental Capacity Analysis Based on Real-world Data

Power battery degradation is inevitable during usage and it greatly affects the overall performance of the electric vehicle (EV). Therefore, reasonable state of health evaluation of power battery plays a vital role in ensuring safe and reliable operation of EVs. In this paper, a robust battery degradation prediction model is established based on real-world operational data of one specific EV. The method overcomes the difficulty lying in data pre-processing and feature extraction by systematically incorporating incremental capacity analysis, Gaussian smoothing and decision tree regression. Results show that the proposed estimation model can accurately predict the driving mileage with the maximum relative absolute error is beneath X%. Considering the low computational requirement of the proposed method, it has great potential to be applied and implemented in real-world battery management system on EV s.