Development and Evaluation of Intelligent Energy Management Strategy for Plug-in Hybrid Electric Vehicle

In this study, the authors propose an intelligent energy management strategy for plug-in hybrid electric vehicles (PHEVs). At the trip level, the strategy takes into account a priori knowledge of vehicle location, roadway characteristics, and real-time traffic information on the travel route from intelligent transportation system technologies in generating a synthesized velocity trajectory for the trip. The synthesized velocity trajectory is then used to determine charge-depleting control that is formulated as a mixed integer linear programming (MILP) problem to minimize the total trip fuel consumption. The strategy can be extended to optimize fuel consumption at the tour level if a pre-planned travel itinerary for the tour and the information about available battery recharging opportunities at intermediate stops in the tour are available. The effectiveness of the proposed strategy, both for the trip-based and tour-based controls, was evaluated against the existing binary mode energy management strategy using a real-world example trip/tour in Southern California. The evaluation results show that the fuel savings of the proposed strategy over the binary mode strategy are around 10-15%.