Fuel minimization of plug-in hybrid electric vehicles by optimizing drive mode selection

Plug-in hybrid electric vehicles (PHEVs) are a viable energy efficient means of transportation, which enjoy both convenience of fuel refilling and cheap electrical energy. But PHEVs have complex dynamics of orchestrating hybrid energy sources. While many prior results in energy management consider the internal optimization processes of PHEVs, this paper focuses on a driver-centric approach that enables the drivers to select the appropriate drive modes for minimizing fuel consumption. Drive modes are driver-selectable pre-set profiles of configurations of powertrain and vehicle parameters. Typical PHEVs have options of drive modes, for example, electric vehicle (EV) mode (that draws fully on battery) and charge sustaining (CS) mode (that utilizes internal combustion engine to charge battery while propelling the vehicle). We develop optimization algorithms that optimize drive mode selection based on trip information, and integrated with path planning to consider intermediate filling and charging stations. We also provide an online algorithm that requires minimal a-priori trip information. We implement our system and evaluate the results empirically on a Chevrolet Volt, which can enable a significant improvement in fuel efficiency.