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纵向滑移工况下的智能轮胎原型

Intelligent Tire Prototype in Longitudinal Slip Operating Conditions.

作者信息

Bastiaan Jennifer, Chawan Abhishek, Eum Wookjin, Alipour Khalil, Rouhollahi Foroogh, Behroozi Mohammad, Baqersad Javad

机构信息

Mechanical Engineering Department, Kettering University, Flint, MI 48504, USA.

出版信息

Sensors (Basel). 2024 Apr 23;24(9):2681. doi: 10.3390/s24092681.

Abstract

With the recent advances in autonomous vehicles, there is an increasing need for sensors that can help monitor tire-road conditions and the forces that are applied to the tire. The footprint area of a tire that makes direct contact with the road surface, known as the contact patch, is a key parameter for determining a vehicle's effectiveness in accelerating, braking, and steering at various velocities. Road unevenness from features such as potholes and cracks results in large fluctuations in the contact patch surface area. Such conditions can eventually require the driver to perform driving maneuvers unorthodox to normal traffic patterns, such as excessive pedal depressions or large steering inputs, which can escalate to hazards such as the loss of control or impact. The integration of sensors into the inner liner of a tire has proven to be a promising method for extracting real-time tire-to-road contact patch interface data. In this research, a tire model is developed using Abaqus/CAE and analyzed using Abaqus/Explicit to study the nonlinear behavior of a rolling tire. Strain variations are investigated at the contact patch in three major longitudinal slip driving scenarios, including acceleration, braking, and free-rolling. Multiple vertical loading conditions on the tire are applied and studied. An intelligent tire prototype called KU-iTire is developed and tested to validate the strain results obtained from the simulations. Similar operating and loading conditions are applied to the physical prototype and the simulation model such that valid comparisons can be made. The experimental investigation focuses on the effectiveness of providing usable and reliable tire-to-road contact patch strain variation data under several longitudinal slip operating conditions. In this research, a correlation between FEA and experimental testing was observed between strain shape for free-rolling, acceleration, and braking conditions. A relationship between peak longitudinal strain and vertical load in free-rolling driving conditions was also observed and a correlation was observed between FEA and physical testing.

摘要

随着自动驾驶车辆的最新进展,对能够帮助监测轮胎与路面状况以及作用在轮胎上的力的传感器的需求日益增加。轮胎与路面直接接触的印迹区域,即所谓的接触斑,是确定车辆在不同速度下加速、制动和转向有效性的关键参数。诸如坑洼和裂缝等特征导致的路面不平整会使接触斑表面积产生大幅波动。这种情况最终可能要求驾驶员采取与正常交通模式不同的驾驶操作,例如过度踩踏板或大幅转向输入,这可能升级为诸如失控或碰撞等危险情况。将传感器集成到轮胎内衬层已被证明是提取实时轮胎与路面接触斑界面数据的一种有前景的方法。在本研究中,使用Abaqus/CAE开发了一个轮胎模型,并使用Abaqus/Explicit进行分析,以研究滚动轮胎的非线性行为。在包括加速、制动和自由滚动在内的三种主要纵向滑移驱动场景下,研究了接触斑处的应变变化。对轮胎施加并研究了多种垂直载荷条件。开发并测试了一种名为KU-iTire的智能轮胎原型,以验证从模拟中获得的应变结果。将相似的运行和载荷条件应用于物理原型和模拟模型,以便能够进行有效的比较。实验研究聚焦于在几种纵向滑移运行条件下提供可用且可靠的轮胎与路面接触斑应变变化数据的有效性。在本研究中,观察到有限元分析(FEA)与实验测试在自由滚动、加速和制动条件下的应变形状之间存在相关性。还观察到自由滚动驾驶条件下峰值纵向应变与垂直载荷之间的关系,并且在有限元分析与物理测试之间观察到了相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69c4/11085535/885e9f082de0/sensors-24-02681-g001.jpg

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