Romagnuolo, Fabio (2025) An integrated tire-vehicle framework: from contact patch modeling to telemetry-based performance evaluation. [Tesi di dottorato]

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Abstract

The dynamic behavior of any vehicle originates at the tire–road interface, where microscopic stress distributions determine the macroscopic forces that govern acceleration, braking, and cornering. Despite extensive research in tire mechanics and vehicle dynamics, a persistent methodological gap still separates the description of tire-level phenomena from their measurable effects at the vehicle scale. This work proposes a physics-based framework that bridges this gap, linking contact-patch mechanics, analytical modeling, and telemetry analysis into a coherent methodology for performance interpretation and setup optimization. At the tire level, an analytical three-dimensional pressure-distribution model was developed to predict how vertical load, inflation pressure, and static camber shape the footprint stress field. The model extends a two-dimensional analytical formulation with geometric parameters representing convexity and centroid shift, ensuring both physical interpretability and calibration efficiency. Its parameters were identified and validated through controlled press experiments using a Tekscan platform, enabling accurate reconstruction of asymmetric pressure profiles and camber-induced variations in local stress. The model provides a quantitative bridge between measurable setup parameters and the underlying grip potential of the tire. At the vehicle level, a MATLAB-based telemetry analysis tool was designed and implemented to standardize data ingestion, filtering, lap segmentation, and KPI computation. The software introduces automated routines for multi-run comparison, delta-time analysis, sector-based decomposition, and corner-phase subdivision, allowing engineers to visualize performance differentials with physical traceability. This environment translates the integration between tire-level physics and vehicle-level telemetry into a reproducible workflow grounded in contact mechanics. The integration of these two levels enabled the definition of a static camber optimization methodology based on telemetry-derived grip-limited samples. By combining model-based pressure fields with measured accelerations, the optimal camber configuration could be estimated for each setup, validated against experimental sessions across multiple vehicles and tracks. The framework was further extended through digital-twin simulations to investigate the influence of tire temperature and wear on handling dynamics. Using validated multi-body models of passenger, sports, and formula cars, the study demonstrated how deviations from optimal tire state significantly affect lateral balance, steady-state cornering stiffness, and transient responsiveness. Temperature variations proved more influential than wear, altering both the magnitude and rate of lateral-force build-up. Overall, the proposed framework integrates analytical modeling, simulation, and telemetry in a unified, physically grounded workflow. It provides a reproducible methodology to interpret vehicle-level performance in terms of tire-level physics, enabling both scientific understanding and industrial decision support. The results demonstrate that reproducibility, physical interpretability, and computational efficiency can coexist within a scalable architecture applicable to diverse vehicle typologies, from road cars to high-performance racing prototypes.

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