Contact Modelling in Multi Body Simulation for Seat Mechanisms

Abstract

Seat mechanisms are the components which enable to adjust seat’s position. Functional simulation aims to reproduce the behaviour of these mechanisms during their normal usages whereas FEA simulations are used for strength prediction. Functional simulation needs a precise description of different components geometry and contact interactions definition between different bodies. The classical approaches by using FEA modelling need a discretization of the geometries. To have a precise representation of the components, the use of fine mesh becomes mandatory for better description of the contact surface. this will lead to a high CPU time and an accuracy issue. Chosen methodology for functional simulation in Faurecia Automotive Seating is multi-body dynamics using Simcenter- 3D Motion software. In this tool two types of contact can be used to define interaction between bodies: analytical contact and 3D contact. The first one is based on Hertzian theory and complicated geometries are approximated by several analytical contacts. Second type of contact is based on a discretization of the real surface by facets. Choice of contact in model can have impact on results. To industrialize the application of Simcenter 3D Motion modelling on different product, a fixed methodology must be defined, specifically, for contact modelling. This work describes the methodology used by Faurecia in multi-body and functional modelling. In the first section a description of different contacts used in Simcenter 3D Motion is presented with a comparison of results between used approaches and the sensitivity of results to different contact settings will be presented. The second section will describe Faurecia methodology and the impact of the contact choice on tracks simulation. The third section presents an application on gear by using different types of contact. A comparison between different approaches is realized. To conclude, some efficiency tools developed using NX Open to automate model preparation based on developed methodology are presented.