Tire-Road Friction Coefficient Estimation under Constant Vehicle Speed Control

被引:13
|
作者
Hu, Juqi [1 ]
Rakheja, Subhash [1 ]
Zhang, Youmin [1 ]
机构
[1] Concordia Univ, Dept Mech Ind & Aerosp Engn, Montreal, PQ, Canada
来源
IFAC PAPERSONLINE | 2019年 / 52卷 / 08期
基金
加拿大自然科学与工程研究理事会;
关键词
Tire-road friction coefficient; Kalman filters; recursive least squares; PID control; REAL-TIME ESTIMATION;
D O I
10.1016/j.ifacol.2019.08.061
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Tire-road friction coefficient (TRFC) is of critical importance for advanced vehicle control systems and autonomous vehicle applications. This paper presents a sequential tire longitudinal stiffness and TRFC estimation method for road vehicles by separate control of the front and rear wheels, for which only standard Kalman filter (KF) and recursive least squares (RLS) techniques are required. While braking torque is actively applied to rear wheels, the proportional-integral-derivative (PID) speed controller dictates the corresponding driving torque to front wheels to compensate the decrease of the vehicle longitudinal speed. Tire force of rear tires are estimated based on the KF, both longitudinal stiffness and TRFC of rear tires are identified using RLS technique. The proposed method has simple structure and the potential of estimating the parameters without severely affecting the vehicle's desired longitudinal speed. Simulation results from vehicle dynamics software CarSim and Matlab/Simulink validate the effectiveness of the proposed method. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:136 / 141
页数:6
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