HEV Power Management Controller Design Based on Game-Theoretic Driver–Powertrain Interaction

This study presents the development and validation of a game theory-based controller for power distribution in hybrid electric vehicles, motivated by the limitations of conventional strategies that rigidly follow driver torque commands. Traditional control methods often assume strict compliance with driver input, which can constrain fuel efficiency. To address this, we propose a Stackelberg game-theoretic model that captures real-time driver-powertrain interaction, where the powertrain acts as a leader optimizing fuel consumption and the driver responds as a follower prioritizing ride comfort. This model introduces controlled deviations from the driver's torque commands to enhance energy efficiency without compromising drivability. The controller dynamically adapts to changing driving conditions without requiring prior route knowledge. Validation was conducted through simulations using a high-fidelity HEV model in MATLAB/Simulink for virtual drivers, and a CarSim-based driving simulator for human drivers. Experiments on urban (SC03) and high-speed (US06) cycles demonstrate that the proposed controller improves fuel economy by up to 5–10% compared to the Equivalent Consumption Minimization Strategy (ECMS), while maintaining high responsiveness as perceived by drivers. These findings highlight the practical potential of game-theoretic energy management in real-world HEV applications.