Modeling discharge characteristics for predicting battery remaining life

Due to the global energy crisis and air pollution, the demand for electric vehicles (EVs) and battery storage systems grows at a gallop. To support this growth, it is important to have an effective exploitation of electrochemical based energy storage system with a reliable battery management system (BMS). The remaining useful life (RUL) prediction and estimation of different age batteries are necessary for BMS design. Terminal voltage, current and surface temperature are three main types of data that have significant impacts on predicting the battery's RUL. In this paper, a mathematical model based on regression analysis is formulated to estimate the batterys RUL. Additionally, the corresponding relationship between discharge curve and battery's age is analyzed base on the battery's capacity variety with using time. Finally, the proposed model is validated with experiments on valve-regulated lead acid (VRLA) batteries.