Taking full advantage of tire saturation in high sideslip drifting maneuvers can substantially improve the handling limits of autonomous vehicles. However, most singular motion control methods in conventional drifting controllers have been conducted, which cannot meet general driving needs. In this article, a hierarchical dynamic drifting controller (HDDC) is designed under both drifting maneuvers and typical cornering maneuvers to uniformly track the general path within and beyond stability limits. Specifically, the HDDC includes the path tracking layer, vehicle motion control layer, and actuator regulating layer. The first layer is designed to achieve accurate path tracking and generate the desired states, and it is algorithmically adaptable and confirmed by MPC and LQR. The second layer is proposed to integrate drifting and typical cornering control by the dynamic drifting inverse model. The third layer can achieve the steering system and wheel speed control to satisfy corresponding commands. Ultimately, the real-time performance of the controller is verified by the ECU hardware-in-the-loop platform. The results with MPC-HDDC and LQR-HDDC show that the HDDC can achieve integrated control of drifting and typical cornering maneuvers and possess high tracking accuracy.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Dynamic Drifting Control for General Path Tracking of Autonomous Vehicles


    Contributors:
    Chen, Guoying (author) / Zhao, Xuanming (author) / Gao, Zhenhai (author) / Hua, Min (author)

    Published in:

    Publication date :

    2023-03-01


    Size :

    16090399 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Autonomous Obstacle Avoidance for Distributed Drive Electric Vehicles via Dynamic Drifting

    Zhao, Xuanming / Chen, Guoying / Gao, Zhenhai et al. | IEEE | 2024


    Hierarchical Adaptive Path-Tracking Control for Autonomous Vehicles

    Chen, Changfang / Jia, Yingmin / Shu, Minglei et al. | IEEE | 2015