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An optimized identification method for modular models of rubber bushings

Cosco, F.I.; Gatti, G.; Toso, A.; Donders, S.; Mundo, D.
ABSTRACT: Rubber bushings are important for automotive manufacturers, for ensuring the vehicle vibration comfort (in terms of vibrations and noise). Ideally the bushing design can be optimized based on virtual simulation models; after all, the more design decisions are taken in an early stage, the lower the design costs (as the physical prototype validation phase can be shortened) and the better the product quality (as earlier decision-making implies still a larger range of feasible design modifications based on the virtual simulations). For this purpose, including rubber bushing behaviour in multibody vehicle dynamic simulations is a crucial task, comprising the solution of two sub-problems: the mathematical modelling to define a constitutive mathematical force-displacement relationship to reproduce the bushing behaviour, and the identification procedure to fit the selected model to the experimental data.
Modular modelling was recently presented as an efficient approach, resulting in a good trade-off between the complexity of the mechanical characteristics of bushing components, and the computational costs required to incorporate bushing component models with sufficient fidelity in the CAE simulation. On the other hand, the state-of-the-art identification procedures can be classified into two main groups: parameterization approaches, requiring an excessive amount of user interaction and expertise, and optimization approaches, which may require a high number of deterministic calculations and involves the risk to not converge to the optimal design.
This paper presents an innovative fast and robust identification tool that relies on efficient-ly combining a parameterization technique with a nonlinear fitting optimization algorithm. It is shown that the results fit very well experimental data reported in recent literature. Moreover, the method compares favorably to other recent prediction methods in terms of computational efficiency, yielding the same (or better) accuracy than prior art.

RASD 2013: Recent Advances in Structural Dynamics XI International Conference, Pisa (Italy), July 1-3 , 2013 Back to Publication List

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