State of Charge Node Planning with Segmented Traffic Information

Abstract

Battery State of Charge (SOC) planning is crucial for the minimization of fuel consumption in Plug-in Hybrid Electric Vehicles (PHEVs). Generally, the charge depleting and charge sustaining strategy is no longer optimal when the required trip energy is greater than the energy stored in a battery. The optimal SOC trajectory depends on the traffic information or the speed profile of the entire trip. In this paper, crude traffic information about the velocity profile, similar to the type of information available in mobile navigation applications, is considered for the SOC planning. Specifically, we propose an effective method of determining the optimal sequence of SOC values at nodes between each segment of a route using segmented sparse traffic information. These SOC node values can be used as boundary conditions or a terminal condition for low-level vehicle energy management with more accurate traffic information available locally. Results from approximate one-hour trip shows that the proposed approach achieves similar fuel consumption improvements (within 2.5%) when compared to solutions from dynamic programming using detailed velocity profiles (with time step every 1 sec). Our proposed method for SOC planning with sparse traffic information improves computation time: from hours to less than a minute.