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首页> 外文会议>EAEC European automotive congress >TIRE STRAIN FE ANALYSIS FOR DEVELOPING THE INTELLIGENT TIRE SYSTEM
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TIRE STRAIN FE ANALYSIS FOR DEVELOPING THE INTELLIGENT TIRE SYSTEM

机译：用于开发智能轮胎系统的轮胎菌株Fe分析

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The tires which are contacted on the road directly are important parts to determine the vehicle behavior. Therefore neglecting defects of tire or information through the tire from the road is the one of main reasons of causing the traffic accidents. In that reason recently the intelligent tire system project named “Apollo project” was started from EU which aims to improve control performance by detecting the strains of tire using the tire sensors. However the tire sensors are not sufficient to measure the strains yet, because of adhesion problem from the difference of stiffness between the tire and sensor and hysteresis of tire. In this research, using FE analysis we estimated the strains which located on the tire sensors and discovered the relations between the strains and driving conditions. Our target tire is 235/65/R17 size for SUV. At first, we performed analyzing of cross-section of target tire and from the result the tire FE model which consists of 8 parts including the ground is generated by IDEAS program. The FE analysis is accomplished using the ABAQUS Standard program. The tire model is constructed as axisymmetric model and analyzed with steady state rolling conditions. Afterward, convergence characteristic of The FE model has to be checked and validation test also has to be performed. The convergence test determined tire model consisted of 40080 nodes and 39600 elements. And the validation test is performed by comparing the vertical stiffness to verify the tire FE model. In the result, the FE model is achieved fewer than 10% error. The Tire strain data were calculated in 3 positions where sensors will be attached in two directions (lateral and circumferential directions). According to the results, increasing the vertical loading causes the larger contact patch length and the speed of tire increases the strains of whole tire elements. And other values (slip ratio, slip angle, camber angle) are predictable from analyzing the changes of strains. Therefore it can be possible to approximate the driving conditions from the tire strain data when the intelligent tire system is developed. In the future, we will make the standardized shape of tire strain and the parameters which determine the strain tendency. And then we plan to build the numerical tire strain model which is for simulations of intelligent tire system. From this research, we estimated the tire strain when tire is rolling and made the data-base to build the numerical tire strain model to develop the intelligent tire system.
机译：直接在道路上接触的轮胎是确定车辆行为的重要部件。因此，通过来自道路的轮胎忽视轮胎或信息的缺陷是导致交通事故的主要原因之一。因此，最近，智能轮胎系统项目名为“Apollo项目”的欧盟开始通过使用轮胎传感器检测轮胎的菌株来提高控制性能。然而，由于轮胎和传感器之间的刚度差和轮胎滞后的刚度差异，轮胎传感器尚不就是测量菌株。在本研究中，使用Fe分析我们估计了位于轮胎传感器上的菌株，并发现了菌株和驾驶条件之间的关系。我们的目标轮胎是SUV的235/65 / R17尺寸。首先，我们执行了目标轮胎的横截面的分析以及由包括地面的8个部分组成的轮胎Fe模型由思想计划产生。使用ABAQUS标准程序完成FE分析。轮胎模型构造为轴对称模型，并用稳态滚动条件分析。之后，还必须检查FE模型的收敛特性，并且还必须执行验证测试。收敛试验确定的轮胎模型包括40080个节点和39600个元素。通过比较垂直刚度来验证轮胎Fe模型来执行验证测试。结果，FE模型误差误差少于10％。在3个位置计算轮胎应变数据，其中传感器将以两个方向（横向和圆周方向）连接。根据结果​​，增加垂直装载导致较大的接触贴片长度，轮胎的速度增加了整个轮胎元素的菌株。和其他值（滑动比率，滑角，副角度）可预测可预测分析菌株的变化。因此，当开发智能轮胎系统时，可以近似于来自轮胎应变数据的驾驶条件。未来，我们将制备轮胎菌株的标准化形状和确定应变趋势的参数。然后我们计划建立用于模拟智能轮胎系统的数值轮胎应变模型。从本研究中，我们估计轮胎滚动时的轮胎应变，并使数据库构建数值轮胎应变模型以开发智能轮胎系统。

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