关键词: 整车耐久试验；K-means 算法；工况划分；用户数据；损伤目标

Abstract: As an important part of the vehicle development process, the vehicle structure durability test plays a crucial role in validating and evaluating the vehicle structure and vehicle systems. It is particularly critical to establish durability test objectives that are user-centered and align with actual user use. This article proposes a method for determining vehicle durability test objectives based on user driving conditions. Firstly, user typical driving conditions and the mileage distribution within each condition are obtained using machine learning clustering algorithms based on actual user driving data. Secondly, real vehicle road spectrum loads are collected on public roads to obtain the corresponding load damage under different driving conditions. Finally, the user driving conditions are correlated with the damage objectives of real vehicle road spectrum loads, resulting in durability test damage objectives that are linked to the user.

Key words: vehicle durability test; K-means algorithm; operating conditions segmentation; user data; damage target