Magic Formula轮胎模型参数辨识的一种混合优化方法

A Hybrid Optimization on Parameters Identification for Magic Formula Tire Model

Magic Formula(MF)轮胎模型能够准确描述轮胎的侧偏特性,广泛应用于车辆动力学的研究。由于MF轮胎模型参数多,且高度非线性,从大量的试验数据中准确辨识这些参数相当困难。提出一种基于遗传算法和数值优化算法的混合优化方法,采用由粗到精的辨识过程,先利用遗传算法得出近似最优解,再利用数值优化算法辨识出精确的参数。利用辨识出的参数计算轮胎的侧偏特性,计算结果与试验数据吻合良好,表明该方法是辨识MF轮胎模型参数的有效手段。

For overcoming the difficulty in identifying the parameters of high nonlinearity Magic Formula （MF） tire model widely used in vehicle dynamics study, a hybrid optimization approach is presented based on genetic algorithm（GA） and numerical optimization algorithm. In the optimization process the approximate optimal solutions are obtained first by using GA, then the accurate parameters are identified by numerical optimization, and finally the tire cornering characteristics are calculated using parameters identified. The results are very close to the experimental data.