Applying the Similarity Method on Pacejka's Magic Formula to Estimate the Maximum Longitudinal Tire-Road Friction Coefficient

• Published in: 2020 American Control Conference (ACC) pp. 218 - 223
• Main Authors: Bardawil, Carine, Daher, Naseem, Shammas, Elie
• Format: Conference Proceeding
• Language: English
• Published: AACC 01.07.2020
• Subjects: Estimation; Friction; Load modeling; Mathematical model; Tires; Vehicle dynamics; Wheels
• ISSN: 2378-5861
• DOI: 10.23919/ACC45564.2020.9147264

This paper focuses on the estimation of the maximum tire-road friction in the tire's longitudinal direction. The proposed estimation scheme relies on readily available on-board sensor measurements, hence it does not require additional hardware. The estimation problem is divided over different subsystems. First, at the chassis motion level, the estimation of the vehicle's longitudinal speed at its center of gravity takes place. Second, based on the wheels rotational dynamics, the longitudinal tire forces and slip ratio are estimated via a state observer design. Information on the longitudinal maximum friction coefficient is then extracted using a model-based identification technique, which relies on Pacejka's Magic Formula tire model and the similarity method. Exponential convergence of the estimation error is guaranteed based on Lyapunov's stability theorem. The implementation and validation of the proposed estimation scheme are carried out in a MATLAB/Simulink® framework via co-simulation with CarSim® . Accelerate-then-brake scenarios are investigated at constant and variable friction levels, ranging from low to high. The obtained results demonstrate the estimator's ability to detect the maximum friction value, even at low tire slip values.