Parameter identification of a lumped parameter thermal model for a permanent magnet synchronous machine

Author

Guemo, Gilles Guedia ; Chantrenne, Patrice ; Jac, Julien

Author_Institution

INSA de LYON, Univ. de Lyon, Villeurbanne, France

fYear

2013

fDate

12-15 May 2013

Firstpage

1316

Lastpage

1320

Abstract

In the thermal modeling of electric machines by lumped parameters, an important step is the tuning of influential poorly known parameters to calibrate the model. The use of Inverse methods based on the minimization of residuals between measured and calculated temperatures is therefore of great help. In this paper, the Gauss-Newton (GN) method, the Levenberg-Marquardt (LM) method and the Genetic Algorithms (GA) method are used to solve this optimization problem in order to identify 10 parameters of a lumped parameter thermal model for a permanent magnet synchronous machine (PMSM).

Keywords

genetic algorithms; inverse transforms; lumped parameter networks; minimisation; parameter estimation; permanent magnet machines; synchronous machines; GA method; GN method; Gauss-Newton method; LM method; Levenberg-Marquardt method; PMSM; electric machines; genetic algorithms; inverse methods; lumped parameter thermal model; minimization; optimization problem; parameter identification; permanent magnet synchronous machine; Equations; Genetic algorithms; Mathematical model; Sociology; Statistics; Stator cores; Temperature measurement; Gauss-Newton method; Genetic algorithms; Levenberg-Marquardt method; electrical machine; inverse method; parameter identification; thermal modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Electric Machines & Drives Conference (IEMDC), 2013 IEEE International

Conference_Location

Chicago, IL

Print_ISBN

978-1-4673-4975-8

Electronic_ISBN

978-1-4673-4973-4

Type

conf

DOI

10.1109/IEMDC.2013.6556329

Filename

6556329