智能轮胎原型在纵向滑动操作条件下使用
Jennifer Bastiaan1, Abhishek Chawan1, Wookjin Eum1
1Mechanical Engineering Department, Kettering University, Flint, MI 48504, USA.
Sensors (Basel, Switzerland)
|May 11, 2024
概括
研究人员开发了一种智能轮胎 (KU-iTire),用于监测轮胎与道路的接触. 模拟和物理测试显示,应力变化与加速和制动等驾驶条件相关,这对于自动驾驶汽车的安全至关重要.
科学领域:
- * 机械工程 机械工程
- * 汽车工程 汽车工程
- * 传感器技术 * 传感器技术
背景情况:
- * 自动驾驶汽车需要先进的传感器来实时监测轮胎路状和力.
- * 轮胎接触区域对于车辆动力学 (加速,制动,转向) 是至关重要的.
- * 道路不规则导致接触点波动,可能导致危险的驾驶情况.
研究的目的:
- * 开发和验证一个与传感器集成的轮胎,用于实时的轮胎与道路接触数据.
- * 在各种驾驶和负载条件下,研究轮胎接触区域内的应变变化.
- *将有限元素分析 (FEA) 结果与智能轮胎原型的实验数据相关联.
主要方法:
- *使用Abaqus/CAE开发轮胎模型,并使用Abaqus/Explicit分析非线性行为.
- * 模拟不同垂直负载下加速,制动和自由滚动场景的应变变化.
- *在类似的运行和加载条件下使用KU-iTire原型进行实验验证.
主要成果:
- * 在自由滚动,加速和制动条件下观察到FEA和对应变形的实验测试之间的相关性.
- *确定了在自由滚动过程中峰值纵向应变和垂直负荷之间的关系.
- * 证明了智能轮胎在提供可靠的接触贴片拉伸数据方面的有效性.
结论:
- *与实验数据相比,FEA模拟准确地预测了轮胎接触贴片拉伸变化.
- * KU-iTire 原型成功捕获实时应变数据,验证了模拟模型.
- * 这项研究为自动驾驶汽车的增强轮胎监控系统提供了基础.
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