Eventos Anais de eventos
COBEM 2023
27th International Congress of Mechanical Engineering
Static Stiffness Correlation of Elastomeric Bushings using Finite Element Analysis
Submission Author:
Luiz Felipe Sallani Simioni , SP
Co-Authors:
Luiz Felipe Sallani Simioni, Wallace Ferreira, Fernando Santos
Presenter: Luiz Felipe Sallani Simioni
doi://10.26678/ABCM.COBEM2023.COB2023-0660
Abstract
The use of bushings in vehicle suspensions is a traditional way to reduce vibration, road noises and increase ride smoothness. However, the bushing design process relies heavily on experimental and historical data due to the complex nature of the elastomers used in it. The use of CAE software in this process is hindered by that complexity, given that the hyperelasticity present in elastomers can only be described using hyperelastic models such as Mooney-Rivlin, Ogden and Yeoh, which use a set of parameters to describe the elastomer’s response. These parameters can be determined using curve fitting procedures that rely on test data, which is not always available and increases development costs and time. The traditional way to simulate a bushing consists of obtaining the geometry and material properties, modeling it in FEA software, applying boundary conditions and analyzing the results - This approach was executed during this work, however, during the research, a few obstacles were faced. For example, the elastomer constitutive behavior needs to be calibrated using experimental data given by its supplier, but this data is often difficult to obtain due to suppliers’ limitations as well as physical limitations such as batch-to-batch rubber stiffness variability, where elastomers with the same Shore A hardness present different stiffnesses. These problems can be avoided by using an inverse analysis instead of the traditional direct method. The present work proposes a trust region dog-leg optimization routine that uses a MATLAB-ABAQUS interaction to find the hyperelastic parameters for a given geometry based on experimental or pseudo-experimental data by calculating the discrepancy between the experimental curve and the calculated curve and minimizing it – the so-called inverse analysis. The methodology was applied to several example models such as a 3D and axisymmetric models of automotive bushings using different types of data: experimental and pseudo experimental, as well as other geometries. It yielded results that showed a minimization of the discrepancy and, therefore, yielded parameters that could describe the constitutive behavior seen in the experimental or pseudo experimental data.
Keywords
hyperelastic models, Optimization, bushing stiffness
