Path-forecasting for HEV optimal energy management (POEM)

This paper studies a control strategy using path-forecasting for Hybrid Electric Vehicle (HEV) optimal energy management (POEM). In the previous work, a receding horizon control (RHC) approach was developed to solve a dynamic programming (DP) formulated optimization problem where preview information of an intended route is utilized to schedule battery state of charge (SoC) usage profile along the route for optimal fuel economy of HEVs. This paper presents our recent work that further developed POEM strategy with refined route segmentation rules and fuel consumption estimation. The work also contains the development of a simulation platform integrating POEM strategy with a production level vehicle control strategy, fuel economy evaluation of POEM under different driving cycles, and the robustness study of the POEM strategy.