Iterative Estimation of the Tire-Road Friction Coefficient and Tire Stiffness of Each Driving Wheel

Abstract

Real-time estimation of tire-road friction coefficients is essential for vehicular active safety systems to achieve better performance such that safe driving is guaranteed. However, real-time estimation of tire-road friction coefficients is challenging due to highly nonlinear and uncertain tire dynamics, and diverse operating conditions of tires. In this paper, we propose an iterative estimation scheme for each driving wheel based on the modified brush tire model which is suitable for the combined longitudinal and lateral motion and consists of only two parameters, i.e. the longitudinal stiffness and the tire-road friction coefficient. Two separate Lyapunov-based estimators are designed to estimate one parameter at a time, assuming the other is known. Then these two estimators are connected together to perform iterative estimation for both parameters. Simulations for various driving scenarios are carried out, including forward acceleration, simultaneous acceleration and turning, and split-mu test. The results show that satisfactory performance is achieved for each driving wheel despite the existence of non-parametric tire model uncertainties.