The University of Southampton
University of Southampton Institutional Repository

Variance-based robust optimization of a permanent magnet synchronous machine

Variance-based robust optimization of a permanent magnet synchronous machine
Variance-based robust optimization of a permanent magnet synchronous machine
This paper focuses on the application of the variance-based global sensitivity analysis for a topological derivative method in order to solve a stochastic nonlinear time-dependent magnetoquasi-static interface problem. To illustrate the approach a permanent magnet (PM) synchronous machine has been considered. Our key objective is to provide a robust design of the rotor poles and of the tooth base in a stator for the reduction of the torque ripple and electromagnetic losses, while taking material uncertainties into account. Input variations of material parameters are modeled using the polynomial chaos expansion technique, which is incorporated into the stochastic collocation method in order to provide a response surface model. Additionally, we can benefit from the variance based sensitivity analysis. This allows us to reduce the dimensionality of the stochastic optimization problems, described by the random-dependent cost functional. Finally, to validate our approach, we provide the 2-D simulations and analysis, which confirm the usefulness of the proposed method and yield a novel topology of a PM synchronous machine.
Chaos Polynomials, Design optimization, Permanent magnet (PM) motors, Robustness, Stochastic processes, Topological derivative, Uncertainty quantification
0018-9464
Putek, Piotr
c6a8a4f3-b5ed-41a8-b794-89b2008653c6
ter Maten, E. Jan W.
b6c3fabb-f985-4524-9738-46ff55445733
Gunther, Michael
bd465c26-bb7a-4682-b7c8-2ef21b0e4a9e
Sykulski, Jan
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
Putek, Piotr
c6a8a4f3-b5ed-41a8-b794-89b2008653c6
ter Maten, E. Jan W.
b6c3fabb-f985-4524-9738-46ff55445733
Gunther, Michael
bd465c26-bb7a-4682-b7c8-2ef21b0e4a9e
Sykulski, Jan
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb

Putek, Piotr, ter Maten, E. Jan W., Gunther, Michael and Sykulski, Jan (2017) Variance-based robust optimization of a permanent magnet synchronous machine. IEEE Transactions on Magnetics, 54 (3). (doi:10.1109/TMAG.2017.2750485).

Record type: Article

Abstract

This paper focuses on the application of the variance-based global sensitivity analysis for a topological derivative method in order to solve a stochastic nonlinear time-dependent magnetoquasi-static interface problem. To illustrate the approach a permanent magnet (PM) synchronous machine has been considered. Our key objective is to provide a robust design of the rotor poles and of the tooth base in a stator for the reduction of the torque ripple and electromagnetic losses, while taking material uncertainties into account. Input variations of material parameters are modeled using the polynomial chaos expansion technique, which is incorporated into the stochastic collocation method in order to provide a response surface model. Additionally, we can benefit from the variance based sensitivity analysis. This allows us to reduce the dimensionality of the stochastic optimization problems, described by the random-dependent cost functional. Finally, to validate our approach, we provide the 2-D simulations and analysis, which confirm the usefulness of the proposed method and yield a novel topology of a PM synchronous machine.

Text
IEEE-TMag-Putek-2017 - Accepted Manuscript
Download (1MB)

More information

Accepted/In Press date: 8 August 2017
e-pub ahead of print date: 27 September 2017
Keywords: Chaos Polynomials, Design optimization, Permanent magnet (PM) motors, Robustness, Stochastic processes, Topological derivative, Uncertainty quantification

Identifiers

Local EPrints ID: 416643
URI: http://eprints.soton.ac.uk/id/eprint/416643
ISSN: 0018-9464
PURE UUID: a629cff6-8f66-48f0-987a-03caab817acb
ORCID for Jan Sykulski: ORCID iD orcid.org/0000-0001-6392-126X

Catalogue record

Date deposited: 03 Jan 2018 17:32
Last modified: 06 Jun 2024 01:32

Export record

Altmetrics

Contributors

Author: Piotr Putek
Author: E. Jan W. ter Maten
Author: Michael Gunther
Author: Jan Sykulski ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×