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Small overlap assessment for early design phases based on vehicle kinematics

机译:基于车辆运动学的早期设计阶段小重叠评估

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Assessing the effectiveness of a vehicle structure concerning the minimisation of intrusions during the early phase of crashworthiness design is challenging because of the lack of a detailed layout of the structural components. In the case of the IIHS Small Overlap Frontal (SOF) crash test, the vehicle kinematics, specifically, the instantaneous positions of the occupant compartment relative to the barrier, are available even early in the development. Hence it is proposed here to use these vehicle kinematics as a predictor of the resulting structural intrusions at the occupant compartment. For this, a method is presented to distinguish between two kinematic responses, glance-off and deformation mode, and identified them by an automated video analysis. This is validated by an example using 182 vehicles subjected to the SOF crash test. This categorical definition is used along with the inbuilt kinematic parameters to derive a linear model for the prediction of the intrusions at the Upper and Lower Hinge Pillar, Upper Dash and Left Instrument Panel providing a first estimate of the vehicle structural rating and thus, overcoming the lack of knowledge uncertainties inherent to this design phase.
机译:根据缺乏结构部件的详细布局,评估关于持续阶段的持续阶段的侵入性最小化入侵最小化的车辆结构的有效性是具有挑战性的。在IIHS小重叠前(SOF)碰撞试验中,车辆运动学,具体地,乘员室相对于屏障的瞬时位置,甚至在开发中可用。因此,在此提出将这些车辆运动学用作乘员室中所产生的结构侵入的预测因子。为此,提出了一种方法以区分两个运动响应,扫描截止和变形模式,并通过自动视频分析识别它们。这通过使用经过SOF碰撞试验的182辆汽车的示例验证。该分类定义与内置的运动学参数一起使用,以导出用于预测上铰链柱,上部划线和左仪表板的入侵的线性模型,其提供了第一估计车辆结构额定值,因此克服了缺乏这种设计阶段固有的知识不确定性。

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