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<p>To improve trajectory tracking accuracy, energy efficiency, and driving safety in distributed drive intelligent vehicles, this study utilizes a volumetric Kalman filter for estimating tire lateral force and implements real-time correction of tire cornering stiffness. This method enhances the vehicle's ability to adapt to nonlinear forces and improves controller precision. The upper layer incorporates Nash game theory, where the vehicle angle and yaw moment act as opposing players. Furthermore, a weight coefficient for the fuzzy control coordination game is employed to ensure precise trajectory tracking and driving safety under various conditions. The lower layer formulates a safety-energy efficiency coordinated control strategy that considers multiple constraints, taking into account road adhesion limits and motor peak torque limits. An optimal torque distribution model is established based on dynamic programming to ensure energy distribution within physical constraints. To validate the strategy, a CarSim/Simulink joint simulation platform is utilized to conduct tests under double lane change and serpentine conditions. The results indicate that the proposed distributed drive electric vehicle steering and yaw coordination control system, utilizing a Nash game framework to prioritize safety and energy efficiency, significantly improves vehicle trajectory tracking accuracy while enhancing energy efficiency and driving safety.</p>

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Research on Steering and Yaw Coordination Control Strategy of Distributed Drive Electric Vehicles Considering Safety and Energy Efficiency Based on Nash Game

  • 期刊论文

  • 发表日期：

    2025年7月18日

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  • Xuanyao Wang,
  • Enze Tao

摘要

To improve trajectory tracking accuracy, energy efficiency, and driving safety in distributed drive intelligent vehicles, this study utilizes a volumetric Kalman filter for estimating tire lateral force and implements real-time correction of tire cornering stiffness. This method enhances the vehicle's ability to adapt to nonlinear forces and improves controller precision. The upper layer incorporates Nash game theory, where the vehicle angle and yaw moment act as opposing players. Furthermore, a weight coefficient for the fuzzy control coordination game is employed to ensure precise trajectory tracking and driving safety under various conditions. The lower layer formulates a safety-energy efficiency coordinated control strategy that considers multiple constraints, taking into account road adhesion limits and motor peak torque limits. An optimal torque distribution model is established based on dynamic programming to ensure energy distribution within physical constraints. To validate the strategy, a CarSim/Simulink joint simulation platform is utilized to conduct tests under double lane change and serpentine conditions. The results indicate that the proposed distributed drive electric vehicle steering and yaw coordination control system, utilizing a Nash game framework to prioritize safety and energy efficiency, significantly improves vehicle trajectory tracking accuracy while enhancing energy efficiency and driving safety.