The Study on individual wheel tire-road friction coefficient estimation based on Brush longitudinal tire model

碩士 === 國立交通大學 === 電控工程研究所 === 103 === This thesis presents four algorithms for real-time estimation of the tire-road friction coefficient of each individual wheel based on the brush longitudinal tire model. These algorithms include 1) a tire-road friction coefficient estimator based on the longitudi...

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Bibliographic Details
Main Authors: Yang, Je-Wei, 楊哲維
Other Authors: Hsiao, Te-Sheng
Format: Others
Language:zh-TW
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/77640772031991597667
Description
Summary:碩士 === 國立交通大學 === 電控工程研究所 === 103 === This thesis presents four algorithms for real-time estimation of the tire-road friction coefficient of each individual wheel based on the brush longitudinal tire model. These algorithms include 1) a tire-road friction coefficient estimator based on the longitudinal tire force and Lyapunov theorem under the assumption of known tire longitudinal stiffness, 2) a feedback connection of a tire-road friction coefficient estimator and a tire longitudinal stiffness estimator for the case of unknown tire longitudinal stiffness. The longitudinal stiffness will be estimated by an estimator. The tire-road friction coefficient estimator and the longitudinal stiffness estimator are connected and form an estimated system. 3) an estimator for simultaneous tire-road friction coefficient and longitudinal stiffness estimation, and 4) an optimization algorithm exploring the relation between tire normal forces and longitudinal stiffness. The performance is verified by simulations based on a 14-DOF complex nonlinear vehicle model and magic formula. Simulation results show that the proposed algorithms are able to correctly estimate the tire-road friction coefficient of each driving wheel when the vehicle is accelerating/decelerating along a straight line. However, the performance deteriorates whenever the vehicle is under a combined motion of turning and accelerating/decelerating.