A Stochastic Approach to Designing Robust Automotive Structures Considering Variability

In the past vehicle structures were overdesigned with large safety factors to ensure proper function and performance for any kind of tolerance conditions (material, geometric, assembly, etc.). This meant OEMs were accepting an unnecessary weight penalty. With ever stricter emission standards and continued vehicle electrification, these weight penalties are no longer acceptable, so OEMs are forced to look at other approaches to ensure robust designs. Therefore, a lot of work has been done in the recent past to better understand the level of variability on component and system levels. Now this understanding needs to be transferred into the product design process which heavily depends on simulation models. The aim of this paper is to demonstrate an approach to ensure robust designs with the understanding of tolerances using a trailer towing attachment as an example. The nominal structure is evaluated and the effects of different types of tolerances compared to the nominal performance is considered. Subsequent stochastic design improvement cycles support gradual robust design changes to the structure, moving it closer to one or more targets and achieving improved performance over the nominal FE analysis. This approach not only allows OEMs to create improved and more robust designs but also helps identify potential weak points, susceptible to variability, so that appropriate quality controls can be implemented in manufacturing plants.