Optimizing the Energy Management Strategy for Plug-In Hybrid Electric Vehicles With Multiple Frequent Routes

Adapting the energy management strategy (EMS) to a specific route is important for plug-in hybrid electric vehicles (PHEVs), because it is usually preferred to apply a blended strategy to use the electricity and fuel energy during the whole trip to maximize the energy efficiency. Studies show that both the route information and human driving style have great impact on vehicle energy consumption. This brief focuses on developing an EMS for PHEVs running on multiple frequent routes, while the controller may not know the destination of each trip beforehand. The human driving style influence can be learned from his or her historical driving data, and the possible future routes as well as their probabilities can be obtained using global positioning system information and historical driving data. An optimal control problem for the higher level PHEV control is formulated and solved. This EMS can be implemented onboard in real time. Simulation results show that it consumes only 2.5% more energy than the posterior global optimal result in an eight-frequent-route scenario without needing to know the destination of each trip in advance.