It is essential for car manufacturers to ensure their vehicle robustness under a daily usage. As no detailed method nor standard prevails, each manufacturer is expected to setup its own methodology for safety parts life-assessment. The early stages of a renewed methodology are proposed in this study. This is based on proving-grounds measurements analysis to quantify the impact of various loads. The method, developed from the load measured at the vehicle wheels, considers the multi-input load case and its variable amplitude content. Measured time-series are analyzed and partitioned into two main categories depending on the time-correlation between the load axes. The driver-induced loads, Driven-Road, (DR) loads, are separated from the effects of random road conditions, Random-Road, (RR) loads. Then, for partition validation, a suitable life quantification method is applied in parallel to the two types of loading. On one hand, an assumption based on strong physical meaning eases the Rainflow Counting method application on the DR load. On the other hand, the use of spectral methods is explored to handle the random loads. This paper details the partition process of the time-series and each of the subsequent validation steps of the method to apply such a partition. Such a validation is performed via a comparison of the pseudo-damage between a referenced signal and the one issued from the partition.

对于汽车制造商而言，确保其车辆在日常使用中的稳健性至关重要。由于没有详细的方法或标准，每个制造商都应该建立自己的安全部件寿命评估方法。本研究提出了更新方法的早期阶段。这是基于试验场测量分析来量化各种负载的影响。该方法是从车轮处测量的载荷发展而来的，考虑了多输入载荷情况及其可变幅度内容。根据负载轴之间的时间相关性，分析测量的时间序列并将其划分为两个主要类别。驾驶员引起的负载，Driven-Road，（DR）负载，与随机道路条件，Random-Road，（RR）负载的影响是分开的。然后，对于分区验证，一种合适的寿命量化方法同时应用于这两种类型的负载。一方面，基于强物理意义的假设简化了雨流计数方法在 DR 负载上的应用。另一方面，探索使用谱方法来处理随机载荷。本文详细介绍了时间序列的划分过程以及应用这种划分的方法的每个后续验证步骤。这种验证是通过比较参考信号和从分区发出的信号之间的伪损坏来执行的。本文详细介绍了时间序列的划分过程以及应用这种划分的方法的每个后续验证步骤。这种验证是通过比较参考信号和从分区发出的信号之间的伪损坏来执行的。本文详细介绍了时间序列的划分过程以及应用这种划分的方法的每个后续验证步骤。这种验证是通过比较参考信号和从分区发出的信号之间的伪损坏来执行的。