Accurate tyre models are important to ensure valid and reliable simulation of vehicle behaviour. To this purpose, the Magic Formula (MF) became the de facto standard for vehicle dynamics simulations, despite requiring many empirically derived coefficients. This paper shows how the accuracy of a simple physical-based brush-type tyre model can be enhanced to simulate tyre behaviour that closely matches MF results. To do so, the real, highly complex rubber friction characteristics are incorporated into the brush model. The friction characteristics were obtained from friction measurements with a tread rubber block. The developed model is validated against experimental tyre data obtained on a flat-track test rig and the corresponding MF model. Results show that the inclusion of friction characteristics allow accurate simulation of longitudinal and lateral slip conditions over a wide range of normal loads with the simple brush model. At extreme loading scenarios, the simulation accuracy deteriorates because of the significant influence of highly nonlinear deformation behaviour of the tyre that is not accounted for in the brush model formulation.


    Access

    Download


    Export, share and cite



    Title :

    Enhancing brush tyre model accuracy through friction measurements


    Contributors:

    Published in:

    Vehicle System Dynamics ; 60 , 6 ; 2075-2097


    Publication date :

    2022-06-03


    Size :

    23 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





    Rubber Friction Law Identification from Tyre Force Measurements Using a Stochastic Brush Model

    Sanders, Tom / Knowles, James / Mavros, Georgios | Springer Verlag | 2024


    Advanced brush tyre modelling

    Romano, Luigi | TIBKAT | 2022


    Parameter optimization of a tyre brush model based on test bench measurements

    Szabo,B. / Tech.Univ.Budapest,HU | Automotive engineering | 2013



    3D brush model to predict longitudinal tyre characteristics

    Riehm, Patrick / Unrau, Hans-Joachim / Gauterin, Frank et al. | Taylor & Francis Verlag | 2019