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Identification of a piecewise affine model for the tire cornering characteristics based on experimental data

机译:基于实验数据的轮胎转弯特性识别分段仿射模型

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摘要

Tire cornering characteristics have significant influence on vehicle lateral dynamics control. Unlike traditional tire mechanics models which are established based on the research experience or the mechanics mechanism, in this study, a novel experimental data-driven modeling approach is presented to model the tire cornering characteristics based on piecewise affine (PWA) identification method. In this approach, the highly nonlinear dynamic of the tire cornering characteristics is well approximated by several affine submodels acting on different regions. To obtain the experimental data which can accurately reflect the tire cornering characteristics, the tire tests are firstly carried out through a high-performance flat-plate test bench. On this basis, the PWA identification of the tire cornering characteristics is composed of the data clustering, the parameter estimation of the affine submodels and the calculation of the hyperplane coefficient matrices. The simulation results of the PWA identification model are finally compared with the experimental data to illustrate that the identified model has high accuracy in approximating the tire nonlinear cornering characteristics under wide range driving conditions.
机译:轮胎转弯特性对车辆横向动力量控制具有显着影响。与基于研究经验或力学机制建立的传统轮胎力学模型不同,在本研究中,提出了一种基于分段仿射(PWA)识别方法的轮胎转弯特性模拟了一种新的实验数据驱动的建模方法。在这种方法中,由作用于不同区域的几个仿射子模型,轮胎转弯特性的高度非线性动态很好地近似。为了获得可以精确地反射轮胎转弯特性的实验数据,首先通过高性能平板测试台进行轮胎测试。在此基础上,轮胎转换特性的PWA识别由数据聚类,仿射子模沟的参数估计和超平面系数矩阵的计算。最终将PWA识别模型的仿真结果与实验数据相比,以说明所识别的模型具有高精度,在宽范围的驾驶条件下近似轮胎非线性转弯特性。

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