Temperature Influence on Tire and Vehicle Lateral Dynamic Performance

Nowadays in an automotive industry that is constantly growing in competition and where the vehicle development stages are reaching very high levels of complexity, it is even more important, for the manufacturers, to be able to quickly compare the results of experimental tests performed on the road in different conditions. A significant amount of time can be saved if robust simulation tools that can compensate the effects of external factors on the acquired data are available. In such a framework, the target of this master thesis is to study how the asphalt temperature influences the tire and the vehicle lateral dynamic performance. Moreover, it is needed to create a corrective algorithm so that the outcomes of every test executed at a random asphalt temperature can be transposed to the reference one (25°C). This project is the result of an eight-months internship in Stellantis NV, more specifically, in the vehicle dynamics division at the FCA Balocco Proving Ground and is mainly divided into three parts. The first one, that was preceded by a deep bibliographical research, is dedicated to the identification of an analytical model able to capture the phenomenon accurately. To work on this task, many experimental tests were performed and a wide database of measurements was built. The second section is focused on the generalization and optimization of the model just defined. It has to become applicable on a large number of vehicle categories requiring, for every correction that has to be done, the lowest amount of data possible. In this phase a short statistical analysis was also made. Finally the third and last part is devoted to the implementation of the compensative tool in a MatLab bicycle model. The goal is to update the measured values of the numerical transfer functions that describe the dynamic behavior of the vehicle during the test and compare the results with the original curves.