Bridging Simulation And Reality: Incorporating Seal Contact Detachment Into Stick–Slip Prediction

Preventing stick–slip in virtual vehicle development combines virtual displacement data with experimental sliding tests. If the calculated relative displacement at a contact exceeds the distance of two stick–slip impulses, that contact could be a potential noise source. Such risks can be mitigated only by design changes or alternative sealing concepts. Stick–slip tests provide the experimental reference, showing how often a frictional pairing produces impulses over a defined sliding distance. The basis for this assessment is Multibody Dynamics (MBD) simulations, which compute component deformations during virtual drives and derive relative displacements at contact interfaces (e.g. in the sealing gap between body and closure), representing the theoretical sliding distance that enables stick–slip effects. Yet, this combined approach has overlooked a critical factor: the deformability of automotive seals. Due to their elastomeric properties and geometry, seals can elastically follow relative movements of surrounding body parts up to a threshold, without frictional sliding at the interface. Only when this threshold is exceeded does stick-slip occur and generate noise. In the virtual vehicle development, the standard stick-slip focus only on the constant relative displacement phase. The new approach focus on the phase where the direction of motion is changing. Therefore, realistic assessment requires not only the average sliding distance between two oscillations but also the relative displacement needed to reach the first slip. To address this, a slip-identification algorithm has been developed, allowing determination of the displacement to first slip under specific loading conditions. This paper provides insights into the new algorithm. Integrating this parameter into stick–slip risk assessment represents a qualitative step forward in early body-in-white development. It supports more accurate prediction of seal-related noise issues, reduces customer complaints, and can be applied both in simulation-based design and in experimental material optimization.