Optimal power management of plug-in hybrid electric vehicles with trip modeling

Hybrid electric vehicles (HEV) have demonstrated their capability of improving the fuel economy and emission. The Plug-in HEV (PHEV), utilizing more battery power, has become a more attractive upgrade of HEV. The charge-depletion mode is more appropriate for the power management of PHEV, i.e. the state of charge (SOC) is expected to drop to a low threshold when the vehicle reaches the destination of the trip. In the past, the trip information has been considered as future information for vehicle operation and thus unavailable a priori. This situation can be changed by the current advancement of Intelligent Transportation Systems (ITS) based on the use of on-board GPS, GIS and advanced traffic flow modeling techniques. In this paper, a new approach of optimal power management of PHEV in the charge-depletion mode is proposed with driving cycle modeling based on the historic traffic information for the highway portion and the traffic lights signals information for the local road portion. A dynamic programming (DP) algorithm is applied to reinforce the charge-depletion control such that the SOC drops to a specific terminal value at the final time of the cycle. The vehicle model was based on a hybrid SUV. Only fuel consumption is considered for the cur-rent stage of study. For the local road part, a trip modeling scheme was developed based on the synchronization with the traffic signals. Simulation study was conducted for several standard driving cycles, and their for air example trip. The results showed significant improvement in fuel economy compared with a rule-based control and a depletion-sustenance control for most cases. The benefit of using traffic signal in trip modeling was also revealed from the improved fuel economy.