Lifecycle Prediction of Second Use Electric Vehicle Batteries Based on ARIMA Model

For alternative vehicles, such as plug-in hybrid electric vehicles (PHEVs) and electric vehicles (EVs), the high cost of lithium-ion battery packs is one of the major impediments to their market development. Due to the degradation of batteries in the vehicle, their life cycle comes to an end when the energy capacity is not sufficient to fulfill the designed requirements for the vehicle. However, the capacity left in the batteries can still be reused for other energy storage applications that support the management of electrical system. The second use of electric vehicle batteries depends on precise forecast of State-of-Health (SOH) in the future. In this paper, a SOH prediction approach is proposed based on autoregressive integrated moving average (ARIMA) model. At first, through proper selection of model orders, a time series model is estimated based on the training data of previous SOH records. Next, the forecast is performed, and the prediction residue is analyzed to evaluate the obtained model by verifying whether the residue is white noise or not. A case study of battery aging test is conducted to validate the effectiveness and efficiency of the proposed approach.