Parallel-in-time optimization of induction motors

Abstract Parallel-in-time (PinT) methods were developed to accelerate time-domain solution of evolutionary problems using modern parallel computer architectures. In this paper we incorporate one of the efficient PinT approaches, in particular, the asynchronous truncated multigrid-reduction-in-time a...

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Main Authors: Jens Hahne, Björn Polenz, Iryna Kulchytska-Ruchka, Stephanie Friedhoff, Stefan Ulbrich, Sebastian Schöps
Format: Article
Language:English
Published: SpringerOpen 2023-06-01
Series:Journal of Mathematics in Industry
Subjects:
Online Access:https://doi.org/10.1186/s13362-023-00134-5
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author Jens Hahne
Björn Polenz
Iryna Kulchytska-Ruchka
Stephanie Friedhoff
Stefan Ulbrich
Sebastian Schöps
author_facet Jens Hahne
Björn Polenz
Iryna Kulchytska-Ruchka
Stephanie Friedhoff
Stefan Ulbrich
Sebastian Schöps
author_sort Jens Hahne
collection DOAJ
description Abstract Parallel-in-time (PinT) methods were developed to accelerate time-domain solution of evolutionary problems using modern parallel computer architectures. In this paper we incorporate one of the efficient PinT approaches, in particular, the asynchronous truncated multigrid-reduction-in-time algorithm, into a bound constrained optimization procedure applied to an induction machine. Calculation of an optimal motor geometry with respect to its efficiency in the steady state is thus parallelized at each iteration of the optimization algorithm. As a result, a more efficient motor model is obtained about 11 times faster compared to optimization using the standard sequential time stepping.
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spelling doaj.art-fbf46ad55ccf438a92b341a903c082b52023-06-25T11:11:11ZengSpringerOpenJournal of Mathematics in Industry2190-59832023-06-0113111610.1186/s13362-023-00134-5Parallel-in-time optimization of induction motorsJens Hahne0Björn Polenz1Iryna Kulchytska-Ruchka2Stephanie Friedhoff3Stefan Ulbrich4Sebastian Schöps5Department of Mathematics, Bergische Universität WuppertalDepartment of Mathematics, Technische Universität DarmstadtComputational Electromagnetics, Technische Universität DarmstadtDepartment of Mathematics, Bergische Universität WuppertalDepartment of Mathematics, Technische Universität DarmstadtComputational Electromagnetics, Technische Universität DarmstadtAbstract Parallel-in-time (PinT) methods were developed to accelerate time-domain solution of evolutionary problems using modern parallel computer architectures. In this paper we incorporate one of the efficient PinT approaches, in particular, the asynchronous truncated multigrid-reduction-in-time algorithm, into a bound constrained optimization procedure applied to an induction machine. Calculation of an optimal motor geometry with respect to its efficiency in the steady state is thus parallelized at each iteration of the optimization algorithm. As a result, a more efficient motor model is obtained about 11 times faster compared to optimization using the standard sequential time stepping.https://doi.org/10.1186/s13362-023-00134-5Parallel-in-timeOptimizationElectric motors
spellingShingle Jens Hahne
Björn Polenz
Iryna Kulchytska-Ruchka
Stephanie Friedhoff
Stefan Ulbrich
Sebastian Schöps
Parallel-in-time optimization of induction motors
Journal of Mathematics in Industry
Parallel-in-time
Optimization
Electric motors
title Parallel-in-time optimization of induction motors
title_full Parallel-in-time optimization of induction motors
title_fullStr Parallel-in-time optimization of induction motors
title_full_unstemmed Parallel-in-time optimization of induction motors
title_short Parallel-in-time optimization of induction motors
title_sort parallel in time optimization of induction motors
topic Parallel-in-time
Optimization
Electric motors
url https://doi.org/10.1186/s13362-023-00134-5
work_keys_str_mv AT jenshahne parallelintimeoptimizationofinductionmotors
AT bjornpolenz parallelintimeoptimizationofinductionmotors
AT irynakulchytskaruchka parallelintimeoptimizationofinductionmotors
AT stephaniefriedhoff parallelintimeoptimizationofinductionmotors
AT stefanulbrich parallelintimeoptimizationofinductionmotors
AT sebastianschops parallelintimeoptimizationofinductionmotors