Energy-Optimal Control of Plug-in Hybrid Electric Vehicles for Real-World Driving Cycles

Plug-in hybrid electric vehicles (PHEVs) are currently recognized as a promising solution for reducing fuel consumption and emissions due to the ability of storing energy through direct connection to the electric grid. Such benefits can be achieved only with a supervisory energy management strategy that optimizes the energy utilization of the vehicle. This control problem is particularly challenging for PHEVs due to the possibility of depleting the battery during usage and the vehicle-to-grid interaction during recharge. This paper proposes a model-based control approach for PHEV energy management that is based on minimizing the overall CO2 emissions produced-directly and indirectly-from vehicle utilization. A supervisory energy manager is formulated as a global optimal control problem and then cast into a local problem by applying the Pontryagin's minimum principle. The proposed controller is implemented in an energy-based simulator of a prototype PHEV and validated on experimental data. A simulation study is conducted to calibrate the control parameters and to investigate the influence of vehicle usage conditions, environmental factors, and geographic scenarios on the PHEV performance using a large database of regulatory and real-world driving profiles.