Title
Tire State Stiffness Prediction For Improving Path Tracking Control During Emergency Collision Avoidance
Abstract
In this study, a model predictive path tracking control method based on the prediction of tire state stiffness is proposed to improve the path tracking performance at the limit of vehicle dynamics. Considering the influence of the nonlinear properties of tire force on vehicle dynamics, a nonlinear UniTire model is established, based on which a state stiffness 3D look-up table is designed to linearize the nonlinear tire model. The tire state stiffness in the prediction horizon is predicted by the vehicle motion model using the reference path information. A new linear time-varying path tracking control model in the prediction horizon is designed based on the predicted tire state stiffness. A nonlinear model predictive controller and a traditional linear time-varying model predictive controller are also designed and compared with the proposed method to verify the effectiveness and advantage of the latter. Results clearly show an improved control performance of the proposed method compared with the traditional method under the limit condition. Moreover, the calculation speed of the proposed method is faster than that of the nonlinear model predictive control method.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2959043
IEEE ACCESS
Keywords
DocType
Volume
Path tracking, vehicle dynamics, model predictive control, UniTire model, state stiffness prediction
Journal
7
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Shaosong Li100.34
Guodong Wang200.34
Guoying Chen300.34
Hong Chen428056.04
Bang-Cheng Zhang5619.39