DocumentCode :
69915
Title :
A Unified Electromagnetic Inverse Problem Algorithm for the Identification of the Magnetic Material Characteristics of Electromagnetic Devices Including Uncertainty Analysis: A Review and Application
Author :
Abdallh, A.A.-E. ; Dupre, L.
Author_Institution :
Dept. of Electr. Energy, Syst., & Autom., Ghent Univ., Ghent, Belgium
Volume :
51
Issue :
1
fYear :
2015
fDate :
Jan. 2015
Firstpage :
1
Lastpage :
10
Abstract :
Magnetic properties of the electromagnetic devices (EMDs) core material are reconstructed by solving a coupled experimental- numerical electromagnetic inverse problem. However, the measurement noise, as well as uncertainties of the forward model parameters and structure, may result in dramatic recovery errors in the recovered values of the material parameters. In this paper, we review the use of the electromagnetic inverse problem for the identification of the magnetic material characteristics. The inverse algorithm is combined with a generic stochastic uncertainty analysis for a priori qualitative error estimation and a quantitative error reduction. The complete inverse methodology is applied to the identification of the magnetizing B-H curve of the magnetic material of a commercial asynchronous machine. Both numerical and experimental results validate the inverse approach, showing a good capability for magnetic material identification in EMDs. The proposed technique is general and can be applied to a wide range of applications in the electromagnetic community.
Keywords :
asynchronous machines; electromagnetic devices; inverse problems; magnetisation; reviews; stochastic processes; a priori qualitative error estimation; asynchronous machine; coupled experimental-numerical electromagnetic inverse problem; electromagnetic device core material; forward model parameters; magnetic material characteristics; magnetic properties; magnetizing B-H curve; measurement noise; quantitative error reduction; review; stochastic uncertainty analysis; unified electromagnetic inverse problem algorithm; Inverse problems; Linear programming; Magnetic materials; Noise measurement; Stator windings; Uncertainty; Coupled experimental???numerical inverse problem; error reduction; magnetic material characterization; stochastic analysis; uncertainty estimation;
fLanguage :
English
Journal_Title :
Magnetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9464
Type :
jour
DOI :
10.1109/TMAG.2014.2332978
Filename :
6843978
Link To Document :
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