The Design of Open Engineering Systems Lab

University at Buffalo - The State University of New York

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Exploring Mass Trade-Offs in Preliminary Vehicle Design using Pareto Sets

Research Area: Research Publication Year: 2006
Type of Publication: Technical Report Keywords: Exploring Mass Trade-Offs in Preliminary Vehicle Design using Pareto Sets
Authors: Donndelinger, Joseph; Ferguson, Scott; Lewis, Kemper
Our goal in this work is to develop analytical tools to support the definition of balanced and compatible sets of vehicle specifications in the early stages of vehicle development. In this paper, we discuss the development and application of a Technical Feasibility Model (TFM) that may be used in preliminary design to assess the technical feasibility and optimality of specified combinations of vehicle performance targets. For this paper, we have exercised the TFM specifically to explore the relationships between vehicle mass, vehicle performance measures, (such as acceleration, fuel efficiency, and interior roominess), and high-level vehicle design parameters (such as overall exterior dimensions, occupant positions, and selection of a powertrain). The TFM is developed by first applying a Multi- Objective Genetic Algorithm to a multidisciplinary design framework to generate a set of Pareto-optimal design solutions, then applying response surface methods to generate a smooth mathematical representation of the Pareto set, and finally using geometric construction to analyze the position of a test point relative to the representation of the Pareto set. Results of this analysis include an assessment of the feasibility and optimality of the test point as well as a variety of projections from the test point to the representation of the Pareto set that may be used to identify opportunities for refining, relaxing, improving, or prioritizing performance specifications. The mapping between performance space and design space has been preserved, allowing for investigation of relationships between performance specifications and design variable settings
Multidisciplinary Analysis and Optimization Conference