DocumentCode :
1182385
Title :
An Induction Machine Model for Predicting Inverter-Machine Interaction
Author :
Sudhoff, Scott D. ; Aliprantis, Dionysios C. ; Kuhn, B. T. ; Chapman, Patrick L.
Author_Institution :
Purdue University, West Lafayette, IN
Volume :
22
Issue :
3
fYear :
2002
fDate :
3/1/2002 12:00:00 AM
Firstpage :
55
Lastpage :
56
Abstract :
The conventional qd induction motor model typically used in drive simulations is very inaccurate in predicting machine performance, except perhaps for the fundamental component of the current and the average torque near rated operating conditions. Predictions of current and torque ripple are often in error by a factor of two to five. This work sets forth an induction machine model specifically designed for use with inverter models to study machine-inverter interaction. Key features include stator and rotor leakage saturation as a function of current and magnetizing flux, distributed effects in the rotor circuits, and a highly computationally efficient implementation. The model is considerably more accurate than the traditional qd model, particularly in its ability to predict switching frequency phenomena. The predictions of the proposed model are compared to those of the standard qd model and to experimental measurements on a 37 kW induction motor drive.
Keywords :
Distributed computing; Induction machines; Induction motors; Inverters; Magnetic circuits; Magnetic flux; Predictive models; Saturation magnetization; Stators; Torque; Induction motor drives; induction motors; modeling; simulation; squirrel cage motors;
fLanguage :
English
Journal_Title :
Power Engineering Review, IEEE
Publisher :
ieee
ISSN :
0272-1724
Type :
jour
DOI :
10.1109/MPER.2002.4312051
Filename :
4312051
Link To Document :
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