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This paper presents the latest development of using an integrated modeling approach to estimate the statistical ranges of key vehicle dynamics performance in the early design phase. The virtual analytical tools predict the statistical confidence interval for specified ride and handling (R&H) metrics to enable a robust design by concurrently simulating the dimensional tolerance of the structural parts as well as the compliance variation. The compliance variation can be defined as load deflection properties of bushings as well as vehicle weight effects on preload. The model can then be used to better represent real world customer experience, allowing prediction of performance ranges relative to targets. In order to better predict these targets, measurements of physical vehicles were made and compared to the model to reveal the actual interactions relative to the theoretical.

During the vehicle development process, dimensional variation simulation modeling has been applied extensively to estimate the effects of build variation on the final product. Traditional variation simulation methods analyze the tolerance inputs of structural components, but do not account for any compliance effects due to stiffness variation in tuning components, such as bushings, springs, isolators, etc., since both product and process variation are simulated based on rigid-body assumptions. Vehicle performance objectives such as ride and handling (R&H) often involve these compliance metrics. The objective of this paper is to present a method to concurrently simulate the tolerance from the structural parts as well as the variability of compliance from the tuning components through an integration package. The combination of these two highly influential effects will allow for a more accurate prediction and assessment of vehicle performance.