Identification Method of Tire-Road Adhesion Coefficient Based on Tire Physical Model and Strain Signal for Pure Longitudinal Slip
DOI:
https://doi.org/10.5545/sv-jme.2024.1036Keywords:
intelligent tire, tire-road adhesion coefficient estimation, slip point, slip rate, nonlinear regressionAbstract
To precisely calculate the tire-road adhesion coefficient of rolling tires at various slip rates, and enhance the safety and stability of vehicle operation, an approach for estimating the tire-road adhesion coefficient based on strain sensors and brush models was proposed. First, a finite element model of 205/55R16 radial tire was established, and the effectiveness of the model was verified through static ground contact and radial stiffness experiments. Then, the circumferential strain signal of the inner liner centerline of the tire during braking was extracted, utilizing the average peak angle spacing of the first-order and second-order circumferential strain curves, and the contact area length was estimated using the arc length formula. Subsequently, the braking simulation of rolling tires confirmed the asymmetry of pressure distribution within the ground contact area, estimating the position of slip points within the contact area based on arbitrary pressure distribution function and brush model, while nonlinear regression was utilized to fit the estimation function of slip point under various slip rates. Finally, a functional relationship was developed between tire-road adhesion coefficient and slip rate, considering the friction characteristics between tire rubber and road surface, while the friction model used is based on exponential decay. The results suggest that the methods described above enable estimation of the tire-road adhesion coefficient under different slip rates, providing valuable insights for intelligent tire applications in vehicle dynamics control.
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