TY - JOUR A2 - Iqbal, Kamran AU - Wang, Jianfeng AU - Liu, Yiqun AU - Ding, Liang AU - Li, Jun AU - Gao, Haibo AU - Liang, Yuhan AU - Sun, Tianyao PY - 2018 DA - 2018/05/29 TI - Neural Network Identification of a Racing Car Tire Model SP - 4143794 VL - 2018 AB - In order to meet the demands of small race car dynamics simulation, a new method of parameter identification in the Magic Formula tire model is presented in this work, based on an analysis of the Magic Formula tire model structure. A high-precision tire model used for vehicle dynamics simulation is established via this method. It is difficult for students to build a high-precision tire model because of the complexity of widely used tire models such as Magic Formula and UniTire. At a pure side slip condition, building a lateral force model is an example, which illustrate the utilization of a multilayer feed-forward neural network to build an intelligent tire model conveniently. In order to fully understand the difference between the two models, a two-degrees-of-freedom (2 DOF) vehicle model is established. The advantages, disadvantages, and applicable scope of the two tire models are discussed after comparing the simulation results of the 2 DOF model with the Magic Formula and intelligent tire model. SN - 2314-4904 UR - https://doi.org/10.1155/2018/4143794 DO - 10.1155/2018/4143794 JF - Journal of Engineering PB - Hindawi KW - ER -