One of the challenges in vehicle design is dealing with multiple functional response constraints. For example, in order to design a vehicle exhaust system, the hanger reaction forces subject to dynamic excitations must be well controlled. The hanger reaction forces at the different frequencies vary because of structural variations such as material properties, thickness and dynamic excitations. There are not only a large number of design variables, but also a large number of functional responses at multiple structural locations. In this paper an integrated reliability-based design optimization process for solving large-scale nonlinear problems with large number of variables and multiple functional responses under uncertainty is developed. The new approach takes advantages of the-state-of-the-art technologies, such as variable screening, design of experiment, response surface model, and reliability-based design optimization methods. Three variable screening methods are investigated and discussed in this research, and they are: main effects plot, linear regression and Wu's method. The selection of the best variable screening method depends on the applications. In the exhaust system example, the linear regression is recommended due to its relatively linear behavior. The integrated RBDO approach has been successfully applied to a benchmark vehicle exhaust system design problem for obtaining a reliable design under multiple functional response constraints. Although the problem has only seven design variables, the proposed process is applicable for solving more complicated vehicle NVH (noise, vibration and harshness) problems.
Reliability-based design optimization of a vehicle exhaust system
2004
12 Seiten, 7 Bilder, 6 Tabellen, 10 Quellen
Conference paper
English
Reliability-Based Design Optimization of a Vehicle Exhaust System
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