Mathematical models simulating the handling behavior of passenger cars are extensively used at a design stage for evaluating the effects of new structural solutions or control systems. The main source of uncertainty in these type of models lies in tire–road interaction, due to high nonlinearity. Proper estimation of tire model parameters is thus of utter importance to obtain reliable results. This paper presents a methodology aimed at identifying the magic formula-tire (MF-Tire) model coefficients of the tires of an axle only based on measurements carried out on board vehicle (vehicle sideslip angle, yaw rate, lateral acceleration, speed, and steer angle) during standard handling maneuvers (step-steers, double lane changes, etc.). The proposed methodology is based on particle filtering (PF) technique. PF may become a serious alternative to classic model-based techniques, such as Kalman filters. Results of the identification procedure were first checked through simulations. Then, PF was applied to experimental data collected using an instrumented passenger car.
A Particle Filter Approach for Identifying Tire Model Parameters From Full-Scale Experimental Tests
Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received March 31, 2016; final manuscript received October 30, 2016; published online December 12, 2016. Assoc. Editor: Massimiliano Gobbi.
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Sabbioni, E., Bao, R., Cheli, F., and Tarsitano, D. (December 12, 2016). "A Particle Filter Approach for Identifying Tire Model Parameters From Full-Scale Experimental Tests." ASME. J. Mech. Des. February 2017; 139(2): 021403. https://doi.org/10.1115/1.4035186
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