With the continuous digitalization of the vehicle development process, virtual design methods play an increasingly important role. Representative load profiles, which can be determined for example with the aid of multi-body system simulation, are required for the reliable design and validation of complex elastomeric bearings such as engine mounts for conventional and electrified drive trains. Due to the complex material properties and complex designs of today's elastomer and hydro mounts, the virtual representation of these components is a challenging task.
In already published researches (46th Conference of the "DVM Arbeitsgruppe Betriebsfestigkeit") it could be shown that the current standard characterization of elastomeric bearings using static and dynamic stiffness as well as loss angle is only partly appropriate to build up and parameterize exact models for the virtual load data determination. On the basis of multi-axial load tests of selected engine mounts, which are done at the highly dynamic component test rig of the Chair of Automotive Engineering of the TU Dresden, physical effects with relevance for the durability could be determined. These are multi-axial static, dynamic and transient changes in stiffness and damping properties. With the knowledge of these effects, a complex model was developed which is designed for the representation of high dynamic loads, hydraulic damping and superposition effects of multi-axial excitations. The model is to be used primarily to calculate operating load signals using multi-body system simulation.
Within the context of the research described here, a complex multistep parameter identification procedure based on particle swarm optimization is presented. With this method it is possible to use complex stochastic signals to identify the model parameters. The first step is to determine the static stiffness of the bearing model in the considered main direction. The uniaxial dynamic parameters are identified afterwards. In the following, the dependence of the uniaxial dynamic parameters on the deformation amplitude is evaluated. Finally, the parameters of the model elements are identified which are dependent on the deformation of the secondary directions (multi-axial model components). The described procedure allows a modularization of the complex bearing model, whereby the model complexity can be adapted according to the application.
Multi-axial test rig measurements showed a significant improvement in the image quality of measured load signals compared to standard models for the newly developed model and the parameter identification process. The simulation error is used as evaluation criterion and the signal damage is considered by means of a standard fatigue strength evaluation. Different types of elastomeric and hydromounts are investigated for validation. Furthermore, the simulation quality of the modelling process outside the fitting range is evaluated. With the help of these investigations it can be deduced that the methods work robustly and will be suitable for practical use after a few adjustments. The investigations contribute to an improved and validated digital representation of elastomeric bearings with a focus on load data determination.
Dipl.-Ing. Steven Ernst, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY; Dipl.-Ing. Felix Schmid, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY; Dr.-Ing. Kay Büttner, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY; Prof. Dr.-Ing. Günther Prokop, Chair of Automobile Engineering - Technische Universität Dresden, GERMANY