Optimal power management of plug-in HEV with intelligent transportation system

Abstract

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 Geographical Information Systems (GIS), Global Positioning Systems (GPS) 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. 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 current stage of study. Simulation results showed significant improvement in fuel economy compared with rule-based power management. Furthermore, simulations on several driving cycles using the proposed method showed much better consistency in fuel economy compared to the rule-based control.