A model predictive control algorithm for angle tracking of steer-by-wire vehicles with variable steering ratio and active front steering

被引:0
作者
Wen, Yuhang [1 ]
Jin, Liqiang [1 ]
Li, Andong [1 ]
Zhong, Zhen [2 ]
Zhang, Fei [2 ]
Yin, Changjie [2 ]
Zhang, Yin [2 ]
机构
[1] Jilin Univ, Natl Key Lab Automot Chassis Integrat & B, Changchun 130022, Peoples R China
[2] Inner Mongolia First Machinery Grp Co Ltd, Baotou 014030, Peoples R China
关键词
Steer-by-wire; Variable steering ratio; Fuzzy control; Active front steering; Global fast terminal sliding mode control; Model predictive control; TERMINAL SLIDING MODE;
D O I
10.1007/s40430-025-05522-z
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This paper proposes an integrated approach for enhancing the steering performance of steer-by-wire (SBW) vehicles. Firstly, a new variable steering ratio design is introduced encompassing both low-to-medium and high-speed ranges. The design ensures a constant steady-state yaw rate gain at low-to-medium speeds, achieved via a novel sorting method underpinned by a comprehensive objective evaluation index, and employs fuzzy control (FC) for enhancement at high speeds to meet driver preferences. Next, an active front steering (AFS) controller is designed based on the global fast terminal sliding mode control (GFTSMC) algorithm to improve the vehicle handing stability. Furthermore, a model predictive control (MPC) algorithm is implemented to achieve precise front wheel steering angle tracking. Finally, the proposed integrated approaches are validated through simulations in the CarSim-MATLAB/Simulink environment. The variable steering ratio design enhances steering sensitivity and driving convenience at low speeds, retains a traditional steering feel at medium speeds, and substantially improves driving stability and safety at high speeds. The AFS controller notably enhances handling stability on low-adhesion road by adjust the front wheel steering angle dynamically. Furthermore, it is evident that the MPC algorithm excels in tracking accuracy compared to some other methods, with its reduced root mean square error (RMSE) and mean absolute error (MAE) for a range of signal types.
引用
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页数:18
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