A diagnosis-based approach for tire–road forces and maximum friction estimation

• Published in: Control engineering practice Vol. 19; no. 2; pp. 174 - 184
• Main Authors: Villagra, Jorge, d’Andréa-Novel, Brigitte, Fliess, Michel, Mounier, Hugues
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-02-2011; Elsevier
• Subjects: Active safety; Algebra; Applied sciences; Asymptotic properties; Automatic Control Engineering; Automotive vehicles; Braking; Computer Aided Engineering; Computer Science; Computer science; control theory; systems; Control theory. Systems; Derivatives; Derivatives of noisy signals; Drives; Estimates; Estimating; Exact sciences and technology; Filtering; Friction; Friction estimation; Machine Learning; Mathematics; Mechanical engineering. Machine design; Modeling and Simulation; Modelling and identification; Nonlinear estimation; Optimization and Control; Roads; Shafts, couplings, clutches, brakes; Active safety; Automotive vehicles; Derivatives of noisy signals; Friction estimation; Nonlinear estimation; Motor car; Friction stress; Modeling; Active system; Observer; Friction coefficient; System identification; Safety; Filtering; Braking; Road vehicle; Vehicle driving; Highway; Experimental study; Weight; Tyre; Friction; Asymptotic approximation; Fault diagnostic; Signal to noise ratio; friction estimation; nonlinear estimation; derivatives of noisy signals; automotive vehicles
• ISSN: 0967-0661; 1873-6939
• DOI: 10.1016/j.conengprac.2010.11.005

A new approach to estimate vehicle tire forces and road maximum adherence is presented. Contrarily to most of the previous works on this subject, it is not an asymptotic observer-based estimation, but a combination of elementary diagnosis tools and new algebraic techniques for filtering and estimating derivatives of noisy signals. In a first step, instantaneous friction and lateral forces will be computed within this framework. Then, extended braking stiffness concept is exploited to detect which braking efforts allow to distinguish a road type from another. A weighted Dugoff model is used during these ‘distinguishable’ intervals to estimate the maximum friction coefficient. Very promising results have been obtained in noisy simulations and real experimentations for most of the driving situations.
► A new approach to estimate vehicle tire forces and road maximum adherence is presented. ► We use a combination of elementary diagnosis tools and new algebraic techniques to estimate derivatives of noisy signals. ► Extended braking stiffness concept is exploited to detect which braking efforts allow distinguishing a road type from another. ► A weighted Dugoff model is used during these ‘distinguishable’ intervals to estimate the maximum friction coefficient. ► Very promising results have been obtained simulation and experimentation for most of the driving situations.