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Test rig optimization

  • Designing good test rigs for fatigue life tests is a common task in the auto- motive industry. The problem to find an optimal test rig configuration and actuator load signals can be formulated as a mathematical program. We in- troduce a new optimization model that includes multi-criteria, discrete and continuous aspects. At the same time we manage to avoid the necessity to deal with the rainflow-counting (RFC) method. RFC is an algorithm, which extracts load cycles from an irregular time signal. As a mathematical func- tion it is non-convex and non-differentiable and, hence, makes optimization of the test rig intractable. The block structure of the load signals is assumed from the beginning. It highly reduces complexity of the problem without decreasing the feasible set. Also, we optimize with respect to the actuators’ positions, which makes it possible to take torques into account and thus extend the feasible set. As a result, the new model gives significantly better results, compared with the other approaches in the test rig optimization. Under certain conditions, the non-convex test rig problem is a union of convex problems on cones. Numerical methods for optimization usually need constraints and a starting point. We describe an algorithm that detects each cone and its interior point in a polynomial time. The test rig problem belongs to the class of bilevel programs. For every instance of the state vector, the sum of functions has to be maximized. We propose a new branch and bound technique that uses local maxima of every summand.

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Verfasserangaben:Alexander Belyaev
URN (Permalink):urn:nbn:de:hbz:386-kluedo-39604
Betreuer:Karl-Heinz Kuefer
Sprache der Veröffentlichung:Englisch
Veröffentlichungsdatum (online):17.12.2014
Jahr der Veröffentlichung:2014
Veröffentlichende Institution:Technische Universität Kaiserslautern
Titel verleihende Institution:Technische Universität Kaiserslautern
Datum der Annahme der Abschlussarbeit:16.12.2014
Datum der Publikation (Server):22.01.2015
Freies Schlagwort / Tag:fatigue; optimization
Seitenzahl:VII, 97
Fachbereiche / Organisatorische Einheiten:Fraunhofer (ITWM)
DDC-Sachgruppen:5 Naturwissenschaften und Mathematik / 510 Mathematik
MSC-Klassifikation (Mathematik):49-XX CALCULUS OF VARIATIONS AND OPTIMAL CONTROL; OPTIMIZATION [See also 34H05, 34K35, 65Kxx, 90Cxx, 93-XX]
Lizenz (Deutsch):Standard gemäß KLUEDO-Leitlinien vom 28.10.2014