Decomposition and Coordination to Support Tradespace Analysis for Ground Vehicle Systems

Tradespace analysis is used to define the characteristics of the solution space for a vehicle design problem enabling decision-makers (DMs) to evaluate the risk-benefit posture of a vehicle design program. The tradespace itself is defined by a set of functional objectives defined by vehicle simulations and evaluating the performance of individual design solutions that are modeled by a set of input variables. Of special interest are efficient design solutions because their perfomance is Pareto meaning that none of their functional objective values can be improved without decaying the value of another objective. The functional objectives are derived from a combination of simulations to determine vehicle performance metrics and direct calculations using vehicle characteristics. The vehicle characteristics represent vendor specifications of vehicle subsystems representing various technologies. These functional objectives represent individual objectives in a multi-objective optimization problem (MOP). Since in vehicle design problems the number of functional objectives may exceed forty, the resulting MOP brings computational and decision-making challenges that are not typical when the number of objectives is lower. Among others, the solution to the overall problem in its entirety may be challenging to discover, or the selection of the preferred Pareto design solution may not be as straightforward for DMs due to the difficulty of comparing tradeoff decisions in high dimensions. In effect, in the presence of many objectives, decomposition of the MOP into MOPs with a smaller number of criteria becomes appealing provided solving the subproblems can be coordinated and related to solving the original MOP. In this preliminary study, a decomposition-coordination technique is proposed and applied to support tradespace analysis for a four-objective MOP to illustrate the anticipated benefits when dealing with MOPs having more objectives. An analysis of two lower-dimensional tradespaces leads to the selection of a preferred efficient design in the four-dimensional tradespace.

• Record URL:
  • https://doi.org/10.4271/2022-01-0370
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01487191
• Supplemental Notes:
  • Abstract reprinted with permission of SAE International.
• Authors:
  • de Castro, Philip
  • Stewart, Hannah
  • Turner, Cameron
  • Wiecek, Margaret
  • Hartman, Gregory
  • Rizzo, Denise
  • Gorsich, David
  • Skowronska, Annette
  • Agusti, Rachel
• Conference:
  • WCX SAE World Congress Experience
  • Location: Detroit & Online Michigan, United States
  • Date: 2022-4-5 to 2022-4-7
• Publication Date: 2022-3-29

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Serial:
  • SAE Technical Paper
  • Publisher: Society of Automotive Engineers (SAE)
  • ISSN: 0148-7191
  • EISSN: 2688-3627
  • Serial URL: http://papers.sae.org/

Subject/Index Terms

• TRT Terms: Analysis; Design methods; Mathematical models; Military vehicles; Optimization; Risk assessment; Training simulators; Vehicle performance
• Subject Areas: Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01841696
• Record Type: Publication
• Source Agency: SAE International
• Report/Paper Numbers: 2022-01-0370
• Files: TRIS, SAE
• Created Date: Apr 6 2022 2:18PM