论文信息 - Multidisciplinary Optimization of a Car Component Under NVH and Weight Constraints Using RSM

Multidisciplinary Optimization of a Car Component Under NVH and Weight Constraints Using RSM

One of the important challenges in the auto industry is to reduce the mass of the vehicle while meeting structural performance requirements for crashworthiness, noise, vibration and harshness, etc. In this paper, a multidisciplinary optimisation of a car back-bonnet is investigated by using the response surface method. A car body is fully surface modelled in CATIA and meshed in software. Then, modal analysis of the finite element model is performed by NASTRAN software to find natural frequencies. A frequency map of that component is extracted and compared with a reference map to detect defects. Design of experiments methodology is used for a screening of the design space and for the generation of approximation models using response surface techniques. Therefore, to optimise the model, improvement of the noise, vibration and harshness behaviour and minimisation of the weight are imposed.

[1] Srinivas Kodiyalam. High performance computing for multidisciplinary design optimization and robustness of vehicle structures , 2003 .

[2] Ren-Jye Yang,et al. Experience with sequential stochastic design improvement methods , 2003 .

[3] R. H. Myers,et al. Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[4] Nielen Stander,et al. On the robustness of a simple domain reduction scheme for simulation‐based optimization , 2002 .

[5] Ren-Jye Yang,et al. Optimization of car body under constraints of noise, vibration, and harshness (NVH), and crash , 2000 .

[6] Fabian Duddeck,et al. Multi-Criteria Evolutionary Optimization for Car Body Acoustics , 2005 .

[7] Jaroslaw Sobieszczanski-Sobieski,et al. Multidisciplinary design optimisation - some formal methods, framework requirements, and application to vehicle design , 2001 .