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...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Open Journal of Vehicular Technology |
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| Online Access: | https://ieeexplore.ieee.org/document/11025176/ |
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| _version_ | 1849417714159845376 |
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| author | Junghee Kim Wansik Choi Changsun Ahn |
| author_facet | Junghee Kim Wansik Choi Changsun Ahn |
| author_sort | Junghee Kim |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-1da8a65197c64c50848d2c8bf1f6be87 |
| institution | Kabale University |
| issn | 2644-1330 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Vehicular Technology |
| spelling | doaj-art-1da8a65197c64c50848d2c8bf1f6be872025-08-20T03:32:41ZengIEEEIEEE Open Journal of Vehicular Technology2644-13302025-01-0161568158110.1109/OJVT.2025.357710911025176HEV Power Management Controller Design Based on Game-Theoretic Driver–Powertrain InteractionJunghee Kim0Wansik Choi1Changsun Ahn2https://orcid.org/0000-0003-1455-9270School of Mechanical Engineering, Pusan National University, Busan, South KoreaSchool of Mechanical Engineering, Pusan National University, Busan, South KoreaSchool of Mechanical Engineering, Pusan National University, Busan, South KoreaThis 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.https://ieeexplore.ieee.org/document/11025176/Game theoryhybrid electric vehicleoptimal controlpower management control |
| spellingShingle | Junghee Kim Wansik Choi Changsun Ahn HEV Power Management Controller Design Based on Game-Theoretic Driver–Powertrain Interaction IEEE Open Journal of Vehicular Technology Game theory hybrid electric vehicle optimal control power management control |
| title | HEV Power Management Controller Design Based on Game-Theoretic Driver–Powertrain Interaction |
| title_full | HEV Power Management Controller Design Based on Game-Theoretic Driver–Powertrain Interaction |
| title_fullStr | HEV Power Management Controller Design Based on Game-Theoretic Driver–Powertrain Interaction |
| title_full_unstemmed | HEV Power Management Controller Design Based on Game-Theoretic Driver–Powertrain Interaction |
| title_short | HEV Power Management Controller Design Based on Game-Theoretic Driver–Powertrain Interaction |
| title_sort | hev power management controller design based on game theoretic driver x2013 powertrain interaction |
| topic | Game theory hybrid electric vehicle optimal control power management control |
| url | https://ieeexplore.ieee.org/document/11025176/ |
| work_keys_str_mv | AT jungheekim hevpowermanagementcontrollerdesignbasedongametheoreticdriverx2013powertraininteraction AT wansikchoi hevpowermanagementcontrollerdesignbasedongametheoreticdriverx2013powertraininteraction AT changsunahn hevpowermanagementcontrollerdesignbasedongametheoreticdriverx2013powertraininteraction |