Abstract
This paper presents an industrial application of the analytical target cascading methodology to optimal design of commercial vehicle systems. The design problems concern the suspension of a heavy-duty truck and the body structure of a small bus. The results provide valuable insights in the feasibility of system-level design targets and the adequacy of subproblem design spaces during product development.
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Notes
This is the case for both design examples and all levels presented in this paper.
2On an Intel i7 CPU 860@2.80GHz and 8.00GB RAM, one systemlevel function evaluation (i.e., Radioss simulation) takes 5 seconds on average, and the subproblem solution required 40 function evaluations on average; at the subsystem level, one Optistruct problem solution required 20 seconds on average. Consequently, one ATC iteration requires roughly 4 minutes.
On an Intel i7 CPU 860@2.80GHz and 8.00GB RAM, one system-level function evaluation (i.e., Radioss simulation) takes 7 minutes on average, and the subproblem solution required 50 function evaluations on average; at the subsystem level one function evaluation takes 12 seconds on average, and each of the two subproblems required 800 function evaluations on average; at the component level, computational cost is negligible. Consequently, one ATC iteration requires roughly half a day.
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The authors are grateful for the financial support of Hyundai Motor Company. Such support does not constitute an endorsement by the sponsor of the opinions expressed in this article.
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A previous version of this manuscript was presented at the 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference (September 17-19, 2012, Indianapolis, Indiana).
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Kang, N., Kokkolaras, M., Papalambros, P.Y. et al. Optimal design of commercial vehicle systems using analytical target cascading. Struct Multidisc Optim 50, 1103–1114 (2014). https://doi.org/10.1007/s00158-014-1097-8
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DOI: https://doi.org/10.1007/s00158-014-1097-8