分布式电驱动车辆圆规转向动力学机理与非合作博弈控制策略研究

doi:10.3901/JME.260286

机械工程学报 ›› 2026, Vol. 62 ›› Issue (8): 259-271.doi: 10.3901/JME.260286

• 特邀专辑：汽车线控底盘 • 上一篇下一篇

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分布式电驱动车辆圆规转向动力学机理与非合作博弈控制策略研究

王康¹, 庄伟超¹, 邱照玉¹, 李兵兵¹, 程坤², 王彦霖¹, 殷国栋¹

1. 东南大学机械工程学院南京 211189;
2. 清华大学车辆与运载学院北京 100084

收稿日期:2025-08-10 修回日期:2026-01-11 出版日期:2026-04-20 发布日期:2026-06-12
作者简介:王康,男,1997年出生,博士研究生。主要研究方向为车辆动力学与控制。E-mail:wkang116@163.com;庄伟超,男,1990年出生,博士,副教授,博士研究生导师。主要研究方向为智能汽车决策规划、智能底盘运动控制、经济性驾驶及能量管理、车辆群集网联协同控制。E-mail:wezhuang@seu.edu.cn
基金资助:
国家自然科学基金(52441204,52394262,52502499);长三角科技创新共同体联合攻关(2023CSJGG0900)资助项目。

Research on the Dynamic Mechanism and Non-cooperative Game Control Strategy for Compass Steering of Distributed Drive Electric Vehicles

WANG Kang¹, ZHUANG Weichao¹, QIU Zhaoyu¹, LI Bingbing¹, CHENG Kun², WANG Yanlin¹, YIN Guodong¹

1. School of Mechanical Engineering, Southeast University, Nanjing 211189;
2. School of Vehicle and Mobility, Tsinghua University, Beijing 100084

Received:2025-08-10 Revised:2026-01-11 Online:2026-04-20 Published:2026-06-12

摘要/Abstract

摘要： 分布式电驱动车辆具有轮边扭矩独立可控等特性，能够实现圆规转向等高机动转向运动，显著提升车辆在狭窄空间内的通行能力。针对圆规转向中运动精度与轮胎磨损难以兼顾的矛盾，提出一种基于非合作博弈考虑位移误差和轮胎磨损的控制策略。将圆规转向归纳为两种主要形式，建立三自由度车辆动力学模型，分析动力学机理，确定圆心车轮轮胎力平方和与滑移速度总平方和为控制目标，构建由策略优化层和控制执行层组成的分层控制架构。进一步分析不同形式下各车轮的动力学状态，基于轮速-轮胎力映射关系实现轮胎横纵向力的解耦控制，并确定控制策略的优化目标和约束条件。依托非合作博弈的纳什均衡求解框架，构建优化算法，求解各工况下的最佳前轮转角和轮速，并设计PI控制器实现轮速的精确跟踪。硬件在环测试结果表明，与最小位移误差策略相比，该策略在六种工况下，同样将位移误差都控制在极小范围内，且显著降低轮胎磨损，具有较好的运动精度、实用性和鲁棒性。

关键词: 圆规转向, 动力学机理, 差速控制, 纳什均衡, 分布式电驱动车辆

Abstract: Distributed drive electric vehicles feature independently controllable wheel-end torque, enabling highly maneuverable steering modes such as compass steering and significantly enhancing the vehicle's ability to navigate narrow spaces. To address the inherent trade-off between motion accuracy and tire wear in compass steering scenarios, this paper proposes a control strategy based on non-cooperative game theory that simultaneously considers displacement error and tire wear. The compass steering motion is classified into two representative types, and a three-degree-of-freedom vehicle dynamics model is established to analyze the underlying mechanisms. A hierarchical control architecture is developed, consisting of a strategy optimization layer and an execution control layer, with the sum of squared tire forces on the pivot wheel and the total squared slip velocities of non-pivot wheels defined as the control objectives. The dynamic states of individual wheels under different compass steering types are further examined. A decoupling method for lateral and longitudinal tire forces is realized based on the mapping between wheel speed and tire force, and the corresponding optimization objectives and constraints are formulated. Leveraging a non-cooperative game framework, a Nash equilibrium-based optimization algorithm is designed to compute the optimal front wheel steering angles and wheel speeds under various test scenarios. A PI controller is then applied to ensure accurate wheel speed tracking. Hardware-in-the-loop(HiL) test results show that, compared with the minimum-displacement-error strategy, the proposed method maintains similarly low displacement errors across six test scenarios, while significantly reducing tire wear. The results validate the proposed strategy's high motion accuracy, strong practical applicability, and robust performance.

Key words: compass steering, dynamic mechanism, differential control, nash equilibrium, distributed drive electric vehicles

中图分类号:

U469

王康, 庄伟超, 邱照玉, 李兵兵, 程坤, 王彦霖, 殷国栋. 分布式电驱动车辆圆规转向动力学机理与非合作博弈控制策略研究[J]. 机械工程学报, 2026, 62(8): 259-271.

WANG Kang, ZHUANG Weichao, QIU Zhaoyu, LI Bingbing, CHENG Kun, WANG Yanlin, YIN Guodong. Research on the Dynamic Mechanism and Non-cooperative Game Control Strategy for Compass Steering of Distributed Drive Electric Vehicles[J]. Journal of Mechanical Engineering, 2026, 62(8): 259-271.

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http://www.cjmenet.com.cn/CN/Y2026/V62/I8/259

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分布式电驱动车辆圆规转向动力学机理与非合作博弈控制策略研究

Research on the Dynamic Mechanism and Non-cooperative Game Control Strategy for Compass Steering of Distributed Drive Electric Vehicles

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