FSTire: An Open-Source Magic Formula Parameter Estimation Tool

The Magic Formula (MF) Tire Model has received wide acclaim for vehicle dynamic simulations. However, it requires that the model parameters be determined for a particular tire, which in turn is a difficult task due to the large number of parameters involved. This work presents a study on the use of a Cascading Algorithm for determining the MF parameters, which is later packaged as a parameter estimation tool. Extending findings from previous research, the cascading algorithm aims to combine the strengths of both the Genetic Algorithm and Nelder-Mead Simplex (NMS) algorithm for the tire model fitting process. The algorithm performance is evaluated based on a total of 456 test datasets of six tires from four different manufacturers. The results show good fitting capabilities (86.5% of the fits have a coefficient of determination greater than 0.9) along with capturing the data trends accurately. The tool is being made available to the community to allow fast and easy fitting of tire models and thereby enhance the accuracy of simulations.