A new study on optimisation under uncertainty for vehicle design. (29th November 2005)

• Record Type: Journal Article
• Authors: Fu, Yan
• Is Part Of: International journal of material & product technology. Volume 25:Number 1-3(2006)
• Page Start: 27
• Page End: 41
• Publication Date: 2005-11-29
• Subjects: design optimisation -- uncertainty -- nonlinear uncertain systems -- genetic algorithms -- vehicle design -- side impact design -- response surface methodology -- RSM -- vehicle weight minimisation -- sequential quadratic programming -- hybrid optimisation -- vehicle safety; Manufacturing processes -- Periodicals; Materials -- Testing -- Periodicals; 620.11
• Languages: English
• ISSNs: 0268-1900

Abstract

With continuous improvement of powerful computers, vehicle designs have been addressed using computational methods. This results in more efficient development of a new product. Most simulation-based optimisation generates deterministic optimal designs without considering variability effects. This paper presents a hybrid optimisation under uncertainty method for vehicle side impact design. Nonlinear response surface models are employed as the 'real' models for conducting this study. The main goal is to maintain or enhance the vehicle side impact performance while minimising the vehicle weight under uncertainty. The hybrid method alleviates the computational burden by estimating the objective and constraint functions during the optimisation process through a re-weighting approach. It also combines a genetic algorithm and sequential quadratic programming to achieve the global or near global optimal designs. The efficiency and accuracy of this method are demonstrated by solving a vehicle design problem.