A study of convergence and mapping in preliminary vehicle design
Scott Ferguson, Ashwin P. Gurnani, Joseph Donndelinger, Kemper E. Lewis · International Journal of Vehicle Systems Modelling and Testing · 2005
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.