A Novel Predictive Energy Management Strategy for Electric Vehicles Based on Velocity Prediction

Abstract

Electric vehicles (EVs) are considered to relieve energy crisis, and environmental problems due to their high efficiency, and low emissions, and energy management strategies (EMSs) have been extensively studied to improve the performance of hybrid energy storage systems (HESSs) for EVs. To effectively reduce HESS energy loss, and extend battery life, this paper proposes a predictive EMS (PEMS) for the battery/supercapacitor HESSs. First, the pattern sequence-based velocity predictor is presented to accurately predict the future short-term velocity profile. Second, the PEMS is proposed by formulating an HESS power split optimization problem, where the HESS energy loss, and the battery capacity loss are considered. Third, an improved chaotic particle swarm optimization algorithm is presented to solve the formulated optimization problem. Simulation results demonstrate that, compared with the benchmark, the proposed PEMS can effectively reduce the HESS energy loss, and extend the battery lifetime at the same time.