Towards A Better Understanding Of Mechanical Stress Applied By Passenger Vehicle Customers With Optimized Instrumentation And Relevant Data Post-Processing Methodologies

Abstract

Listen

Translate article

The various mechanical parts of a vehicle must be designed to ensure a target level of reliability compatible with safety objectives while limiting oversizing. This requires automobile manufacturers to implement the relevant methodological tools adapted to the component failure mechanisms. Several improvements have been made over the past 10 years on this topic, in particular with tools taking into account the local properties of materials and thus delivering local stresses and damage at any point of each part. These procedures require track measurements or virtual road load data representing the image that each manufacturer chooses to have of a given customer severity level. This arbitrary level of severity then makes it possible to express a target performance threshold of the component to guarantee objective reliability. The difficulty in these methods is to be able to capture the severity levels of customers all over the world, which is by definition very variable because depending on several inputs like the road geography and quality, the customer behavior and style.The objective of this paper is to share the state-of-the-art methodologies implemented by PSA Groupe (now Stellantis) to capture this information with the best efficiency and also to reduce its cost through a Big Data approach.Three main themes will be addressed:○ Instrumentation strategy○Sampling methodology to catch the reality of the customer’s field○ Objectification and classification of customer life situations