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Multi-objective optimization of a disc brake system by using SPEA2 and RBFN
Department of Mechanical Engineering, School of Engineering, Jönköping University, Jönköping, Sweden.ORCID iD: 0000-0001-7534-0382
Department of Mechanical Engineering, School of Engineering, Jönköping University, Jönköping, Sweden.
Department of Mechanical Engineering, School of Engineering, Jönköping University, Jönköping, Sweden.ORCID iD: 0000-0001-6821-5727
2013 (English)In: ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference: Volume 3B: 39th Design Automation Conference, New York: ASME Press, 2013Conference paper, Published paper (Other academic)
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Text
Abstract [en]

Many engineering design optimization problems involve multiple conflicting objectives, which today often are obtained by computational expensive finite element simulations. Evolutionary multi-objective optimization (EMO) methods based on surrogate modeling is one approach of solving this class of problems. In this paper, multi-objective optimization of a disc brake system to a heavy truck by using EMO and radial basis function networks (RBFN) is presented. Three conflicting objectives are considered. These are: 1) minimizing the maximum temperature of the disc brake, 2) maximizing the brake energy of the system and 3) minimizing the mass of the back plate of the brake pad. An iterative Latin hypercube sampling method is used to construct the design of experiments (DoE) for the design variables. Next, thermo-mechanical finite element analysis of the disc brake, including frictional heating between the pad and the disc, is performed in order to determine the values of the first two objectives for the DoE. Surrogate models for the maximum temperature and the brake energy are created using RBFN with polynomial biases. Different radial basis functions are compared using statistical errors and cross validation errors (PRESS) to evaluate the accuracy of the surrogate models and to select the most accurate radial basis function. The multi-objective optimization problem is then solved by employing EMO using the strength Pareto evolutionary algorithm (SPEA2). Finally, the Pareto fronts generated by the proposed methodology are presented and discussed.

Place, publisher, year, edition, pages
New York: ASME Press, 2013.
Keywords [en]
Multi-objective Optimization, Disc Brake, RBF, RBFN, Surrogate Modelling, Response Surface, Pareto-front
National Category
Applied Mechanics Mechanical Engineering
Research subject
Mechanical Engineering
Identifiers
URN: urn:nbn:se:oru:diva-48246DOI: 10.1115/DETC2013-12809ISI: 000362380400029Scopus ID: 2-s2.0-84896968665ISBN: 978-0-7918-5589-8 (print)OAI: oai:DiVA.org:oru-48246DiVA, id: diva2:904514
Conference
ASME 2013 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE), Portland, Oregon, USA, August 4-7, 2013
Available from: 2013-06-25 Created: 2016-02-15 Last updated: 2017-10-18Bibliographically approved

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Amouzgar, KavehStrömberg, Niclas
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