Research on capacity characteristics and prediction method of electric vehicle lithium-ion batteries under time-varying operating conditions

Abstract

Electric vehicles (EVs) are being increasingly used today but the safety of their battery system remains an issue. Therefore, a clear understanding of the degradation of EV batteries and the correct prediction of their remaining useful life (RUL) is highly desirable. To solve this problem, firstly, the degradation of EV LIBs at different temperatures and discharge rates are studied experimentally. Then, based on the testing results, the output performance and capacity degradation characteristics of LIBs operating under different conditions are analyze, and a new degradation model is proposed to more accurately predict the capacity degradation of EV LIBs. The research discloses that although the available capacity of LIBs generally decreases with the increase of charge-discharge cycles, at the initial stage of battery use, the available capacity of LIBs are show a transient increase with the increase of charge-discharge cycles. Additionally, the temperature has a significant impact on the available capacity of LIBs, and the alternating changes in ambient temperature can accelerate the degradation of LIBs. Moreover, the innovative degradation model proposed by this paper has higher prediction accuracy than the traditional degradation model, for example, the maximum prediction error given by the proposed model is only 1.17 Ah, which corresponds to a relatively error of 2.34 %; by contrast, the maximum prediction error of the traditional dual exponential model is −5.59 Ah, which corresponds to a relatively error of 11.18 %. These new findings are helpful to the future reliability design of the EVs battery systems.