The Role of Velocity Forecasting in Adaptive-ECMS for Hybrid Electric Vehicles

The energy management strategy is crucial in improving the fuel economy of hybrid electric vehicles (HEVs). This paper targets at evaluating the role of velocity forecasting in the adaptive equivalent consumption minimization strategies (ECMS) of HEVs. By predicting the short-term future velocity through a data-driven approach, the energy management controller is able to optimize the equivalence factor online and adapt to current driving situations intelligently. Compared with basic adaptive ECMS approach without velocity forecasting abilities, the proposed strategy is able to foresee the change of the driving behaviors and adjust the equivalence factor more reasonably. Simulation results show that the adaptive ECMS with velocity forecast ability is more sensitive to the driving profiles, and the resultant fuel economy is improved by over 3%.