Design and validation of an adaptive tyre model with influence of temperature for a Formula SAE Vehicle

Tyres are essential components of a race car, being the only direct link between the vehicle and the road. In racing environments, it is crucial to model them with a high accuracy level to maximize the performance of the whole vehicle. Common tyre models, such as Magic Formula, are described by a pure mechanical behaviour, neglecting the influence of parameters such as temperature, which has a big effect on force production capability of tyres. Because of that this master thesis proposes an adaptive thermal tyre model, aimed to improve the estimation of tyre forces produced in the contact patch. First, a tyre surface temperature estimator is proposed, which allows to measure this parameter without sensors and a low computational cost. Starting from works already present in literature, a new lumped parameter model is developed adding improvements. Tyre thermal parameters are explained and estimated using measured data and its performance is evaluated. Then, a modified version of Pacejka's Magic Formula with influence of temperature is proposed, adding new empirical coefficients dependent by temperature. These coefficients are fitted using an updated procedure already used to estimate Magic Formula coefficients. Modified Magic Formula's performance is compared with the base one confirming that the addition of temperature effects results in an improvement of tyre forces estimation.