Probabilistic Prediction and Validation of Vehicle Dynamic Performance by Concurrent Modeling Approach
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.