Identification of tire force characteristics using a Hybrid method

Abstract

The present study applies a Hybrid method for identification of unknown parameters in a semi-empirical tire model, the so-called Magic Formula. Firstly, the Hybrid method used a Genetic Algorithm (GA) as a global search methodology with high exploration power. Secondly, the results of the Genetic Algorithm were used as starting values for the Levenberg-Marquardt (LM) algorithm as a gradient-based method with high exploitation power. In this way the beneficial aspects of both methods are simultaneously exploited and their shortcomings are avoided. In order to establish the effectiveness of the proposed method, performance of the Hybrid method has been compared with other methods available in the literature. In addition, the use of GA as a Heuristic method for tire parameters identification has been discussed. Moreover, the extrapolation power of Magic Formula identified with Hybrid method has been properly investigated. Finally, the performance of the Hybrid method has been examined through tire parameter identification with priori known model. The results indicated that the Hybrid method has outstanding benefits such as high convergence speed, high accuracy, and null-sensitivity to the starting values of unknown parameters.