Electric vehicle battery remaining charging time estimation considering charging accuracy and charging profile prediction

Electric vehicles (EVs) have been growing rapidly in popularity recent years and become a future trend. It is an important aspect of user experience to know the Remaining Charging Time (RCT) EV with confidence. However, it difficult find algorithm that accurately estimates RCT for current market. The maximum estimation error Tesla Model X can be as high 60 min from 10 % 99 state-of-charge (SOC) while charging at direct (DC). A highly accurate electric demand will continue EVs more popular. There are currently two challenges arriving estimate. First, most commercial chargers cannot provide requested currents during constant (CC) stage. Second, hard predict profile voltage (CV) To address first issue, this study proposes updates accuracy online CC stage by considering confidence interval between historical real-time data. solve second battery resistance prediction model profiles CV stage, using Radial Basis Function (RBF) neural network (NN). test results demonstrate proposed achieves reduction 73.6 %–84.4 over traditional method stages, respectively.