Engine mount rubber (EMR) is an important vehicle component to isolate the vehicle structure from engine vibration. The paper deals with optimal design of EMR considering the material stiffness and fatigue strength of a rubber. The objective is to minimize both the weight and the maximum stress of EMR, and to maximize the fatigue life cycle subjected to constraints on the static stiffness of the rubber. A hyperelastic rubber model with a high strain range is used to accommodate the non-linear behaviour of EMR in the stress and fatigue analysis. In the context of approximate optimization, a back-propagation neural network is used to construct global response surfaces between input design variables and output responses of objective functions and constraints. A microgenetic algorithm (MGA) is adopted as a global optimizer in order to consider the inherent non-linearity of analysis model as well. A multi-objective optimization result shows improved design performances regarding the reduction in the maximum stress and the increase in the life cycle with acceptable material stiffness.
|Number of pages||13|
|Journal||Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering|
|Publication status||Published - 2007 Oct 1|
All Science Journal Classification (ASJC) codes
- Aerospace Engineering
- Mechanical Engineering