Treatment of random fatigue stresses and topological optimization of anti-vibration elastomeric components for automobile suspension

Objectives

The overall objective of this project is to develop a virtual methodology that allows for the robust, stable, and agile simulation of the fatigue behavior of elastomers in anti-vibration applications, based on the intrinsic properties of the material itself, road markings, and the geometry of the component.

To achieve the main objective, the following specific objectives will be necessary:

- To obtain a new methodology based on the treatment of random fatigue stresses and topological optimization of anti-vibration elastomer components for automotive suspensions.

- To develop a methodology for simplifying and synthesizing random road markings, based on signals of shorter duration and lower frequency, but with the same impact on the anti-vibration component (development of a complete accelerated model).

- To obtain a new mathematical model for the viscoelastic behavior of rubber based on both a phenomenological (MORPH model) and a physical (DFM model) foundation.

- To theoretically predict the loss of stiffness in elastomeric anti-vibration components during the early design phases due to the degradation of their physical properties, without the need for experimental material characterization.

- To introduce more innovative and efficient designs through the geometric optimization of anti-vibration parts for the automotive sector (using virtual tools such as machine learning).

- To reduce the design and development costs of parts for anti-vibration applications by 60% by using more advanced and comprehensive simulation tools that minimize the time required for the prototyping and validation phases of new products. The goal is to reduce testing time by a factor of 2.5.

- To reduce by 2.5 (60%) the time between when a client requests a new anti-vibration part and when CIKATEK actually obtains a functional prototype that passes the fatigue test. (The number of durability tests, which are time-consuming, costly, and highly difficult, will be reduced.)