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Automotive Engineering ›› 2025, Vol. 47 ›› Issue (12): 2387-2396.doi: 10.19562/j.chinasae.qcgc.2025.12.011

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Yaw Stability Control of Vehicles Under Extreme Working Conditions

Yong Han1,2(),Sihang Xie1,2,Shuiwen Shen1,2,Zhenyu Qin1,2,Di Pan1,2,Zhiqun Yuan1,2   

  1. 1.School of Mechanical and Automotive Engineering,Xiamen University of Science and Technology,Xiamen 361000
    2.Fujian Provincial Key Laboratory of Advanced Design and Manufacturing for Passenger Vehicles,Xiamen 361024
  • Received:2025-03-11 Revised:2025-05-06 Online:2025-12-25 Published:2025-12-19
  • Contact: Yong Han E-mail:yonghan@xmut.edu.cn

Abstract:

A high-speed vehicle running unilaterally over a low traction coefficient road surface (e.g., water or sand) is very likely to cause a large yaw loss of control, and the traditional control system relies on the driver's operation and is not robust enough, resulting in an increased risk of misoperation under emergency conditions. To address this problem, in this paper a front wheel active steering strategy is proposed based on radial basis function neural network sliding mode control (RBF-SMC). Firstly, a two-degree-of-freedom model of the vehicle is established, and the RBF neural network is fused with the sliding mode control, which effectively suppresses the vibration problem of the traditional sliding mode control by approximating the system uncertainty through the adaptive law. Secondly, a nonlinear tire model is established based on the magic tire formula to solve the differential equations of the vehicle dynamics to obtain the dynamic stability domain of the vehicle phase plane, so as to realize that the controller intervenes only when the vehicle is on the verge of going out of control, reducing the interference to the normal operation of the driver. Finally, the control performance of different controllers is compared by double-shifted line conditions, and a folio road condition is designed to simulate the above emergency conditions to verify the effectiveness of the controller proposed in this paper. The simulation results show that this method has better yaw stability control effect than the traditional Sliding Mode Control (SMC) and Linear Quadratic Regulator (LQR).

Key words: yaw stability control, sliding mode control, magic formula model, dynamic stabilization domains, split-μ road condition