Title: A study of convergence and mapping in preliminary vehicle design

Authors: Scott Ferguson, Ashwin Gurnani, Joseph Donndelinger, Kemper Lewis

Addresses: Department of Mechanical and Aerospace Engineering, University at Buffalo, SUNY, Buffalo, NY, USA. ' Department of Mechanical and Aerospace Engineering, University at Buffalo, SUNY, Buffalo, NY, USA. ' Vehicle Development Research Lab, General Motors Research and Development Center, Warren, MI, USA. ' Department of Mechanical and Aerospace Engineering, University at Buffalo, SUNY, Buffalo, NY, USA

Abstract: In this paper, we investigate the issue of convergence in multi-objective optimisation problems developed for vehicle analyses when using a Multi-Objective Genetic Algorithm (MOGA) to determine the set of Pareto optimal automobile configurations. Additionally, given a Pareto set for a multi-objective problem, the mapping between the performance and design space is studied to determine new automobile design configurations for a given set of performance specifications. The advantage of this study is that the automobile|s design information is obtained without having to repeat system analyses. The tools developed in this paper are applied both to a simple multi-objective optimisation problem to illustrate the methodology and to a preliminary vehicle design framework to develop a Technical Feasibility Model (TFM) for use in the early stages of automobile design.

Keywords: multiobjective optimisation; performance space; design space; algorithm convergence; vehicle feasibility; genetic algorithms; vehicle design; design configurations; performance specifications; automobile design; technical feasibility model; design feasibility; preliminary design.

DOI: 10.1504/IJVSMT.2005.008579

International Journal of Vehicle Systems Modelling and Testing, 2005 Vol.1 No.1/2/3, pp.192 - 215

Published online: 04 Jan 2006 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article