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Ing. Guido Napolitano Dell'Annunziata, Ph.D. candidate, University of Naples Federico II
Research Question & Target. Developing reliable tire data to understand their physical behavior is one of the biggest challenges for automotive engineers and testing technicians. In motorsport, maximizing vehicle performance requires operating the tires within an optimal thermal range, which can be difficult to define accurately. In car and tire manufacturing, a trade-off must be struck among multiple complex and interconnected features to ensure safety, optimal friction, and durability. To meet these needs, we propose developing a modular platform based on several models that can provide concrete outputs for motorsport teams and manufacturers. Our platform will aim to speed up tire/vehicle development, minimize iterative testing loops, and objectivize performance. Methodology. In this work three different physical models, developed by the UniNa research group and its spin-off MegaRide, are coupled within a co-simulation framework, allowing to investigate the tire performance sensitivities and to optimize the vehicle behavior in the widest possible range of tire working conditions. First, a tool called T.R.I.C.K. (Tire-Road Interaction Characterization & Knowledge) is presented. This tool had been developed to process data acquired from experimental test sessions, estimating tires interaction forces, slip indices and inclination angle; the output of this tool is a sort of “virtual telemetry” which can be used to feed the thermoRIDE, a thermodynamic model which provides in the output the lateral and circumferential temperature distributions, in all the different tire layers. Then, it is shown how this thermodynamic model can work coupled with a wear model, called weaRIDE, thanks to which it is possible to calculate tire tread thickness variation and to evaluate its effect on tire temperature and pressure. Results. By analyzing the output of these models, it is possible to extract crucial information about the optimal temperature and pressure range for tire operation, which can then be used to define a suitable setup for optimizing vehicle performance. By combining the thermodynamic and wear models, the mutual dependencies between temperature variations and tire degradation can be identified, revealing the conditions under which these two phenomena significantly affect tire and vehicle dynamic behavior. By quantifying the effects of thermodynamics and degradation, it is possible to compare the behavior of different tires under the same conditions or simulate tire behavior under different environmental scenarios, allowing to development of strategies for predicting optimal choices for race weekends. Limitations. The main limitation of this methodology is related to the quality of the data acquired from the vehicle that represents the starting point of the data processing toolchain; poor quality data or sensor malfunctions may make the methodology not applicable; to overcome this limit the authors are conducting further activities, based on the use of AI and state estimators. Furthermore, accurate parameterization of the models is required, through the conduct of dedicated characterization tests, which slightly lengthens the duration of the first application of the models to a given vehicle/tire. Novelties. Building on the authors' previous work, the proposed approach aims to combine different models developed in recent years to create a comprehensive methodology for simulating complex tire behavior with a multi-physical approach. This methodology can be applied to both offline and online simulation platforms. The latest developments of the models focused on creating complete modularity, making it much easier to combine and use them together. Conclusions. This work has presented several physical models that can individually describe and analyze different specific aspects of tire/road interaction phenomena. However, their combination can provide an even more powerful instrument for gaining a comprehensive understanding of such complex themes and obtaining a nearly complete tire digital twin. By employing the T.R.IC.K. tool, thermoRIDE, and weaRIDE models together, it is possible to conduct tire thermal analysis and identify the temperature range at which grip is maximized. This global procedure could be a valuable tool for optimizing vehicle performance and setup, and thus reducing lap times in motorsport race events.
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