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

There has been significant interest in plug-in hybrid electric vehicles (PHEVs) as a means to decrease dependence on imported oil and to reduce greenhouse gases as well as other pollutant emissions. One of the critical considerations in PHEV development is the design of its energy-management strategy, which determines how energy in a hybrid powertrain should be produced and utilized as a function of various vehicle parameters. In this paper, we propose an intelligent energy-management strategy for PHEVs. At the trip level, the strategy takes into account a priori knowledge of vehicle location, roadway characteristics, and real-time traffic conditions 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 battery´s charge-depleting control that is formulated as a mixed-integer linear programming problem to minimize the total trip fuel consumption. The strategy can be extended to optimize vehicle fuel consumption at the tour level if a preplanned travel itinerary for the tour and the information about available battery recharging opportunities at intermediate stops along the tour are available. The effectiveness of the proposed strategy, both for the trip- and tour-based controls, was evaluated against the existing binary-mode energy-management strategy using real-world trip/tour examples in southern California. The evaluation results show that the fuel savings of the proposed strategy over the binary-mode strategy are around 10%-15%.