Parameter Identification of a Lumped Parameter Thermal Model for a Permanent Magnet Synchronous Machine

被引：0
作者：
Guemo, Gilles Guedia [1 ]
Chantrenne, Patrice [2 ]
Jac, Julien [3 ]
机构：
[1] Univ Lyon, CNRS, INSA LYON, Ctr Therm Lyon CETHIL CETHIL UMR 5008, F-69621 Villeurbanne, France
[2] Univ Lyon, CNRS, INSA Lyon, MATEIS,UMR5510, F-69621 Villeurbanne, France
[3] ERNEO, F-34830 Clapiers, France
来源：
2013 IEEE INTERNATIONAL ELECTRIC MACHINES & DRIVES CONFERENCE (IEMDC) | 2013年
关键词：
electrical machine; Genetic algorithms; Gauss-Newton method; inverse method; Levenberg-Marquardt method; parameter identification; thermal modeling;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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).
引用
收藏
页码：1316 / 1320
页数：5
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