Data-Based Identification of the Tire Cornering Properties Via Piecewise Affine Approximation

It is difficult to accurately simulate the cornering performance of a vehicle using a simplified vehicle model; therefore, a proper evaluation process should be conducted from an experimental perspective. In addition, there are several possible combinations of subparts in suspension modules, such as springs, dampers, stabilizers, or other parts, and the characteristic identification of each part may require significant costs and time. In this study, the cornering performance of a vehicle system was experimentally evaluated using several combinations of subparts in the suspension module as well as candidate tire cases. All characteristic parameters used in the two indices were previously identified as separate steps, and vehicle tests were performed according to all the required test scenarios for cornering performance. The evaluation of the cornering performance of a vehicle was proposed using the suspension characteristic cornering performance (SCCP) index and suspension and tire characteristic cornering performance based-on-tests (STCT) index, respectively, using measured data from a vehicle test. The STCT index is revised from the SCCP index by considering the tires’ effects, and the optimal selection of the suspension and tires can be obtained from the proposed indices. The feasibility of the proposed STCT index was verified by evaluating the cornering performance from all the prepared test results.

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Data-Based Identification of the Tire Cornering Properties Via Piecewise Affine Approximation

Cited by 2 publications

References 39 publications

Explicit hybrid MPC for the lateral stabilization of electric vehicle system

Explicit hybrid MPC for the lateral stabilization of electric vehicle system

Optimal Selection of Suspension and Tires for Vehicles’ Cornering Performance

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