DocumentCode
762478
Title
An induction machine model for predicting inverter-machine interaction
Author
Sudhoff, Scott D. ; Aliprantis, Dionysios C. ; Kuhn, Brian T. ; Chapman, Patrick L.
Author_Institution
Dept. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
Volume
17
Issue
2
fYear
2002
fDate
6/1/2002 12:00:00 AM
Firstpage
203
Lastpage
210
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 with those of the standard qd model and to experimental measurements on a 37 W induction motor drive
Keywords
induction motor drives; invertors; machine theory; magnetic flux; magnetic leakage; magnetisation; rotors; squirrel cage motors; stators; torque; 37 kW; 460 V; 60 Hz; 800 V; average torque; current ripple prediction; drive simulations; fundamental current component; inverter models; leakage path magnetics; machine performance prediction; machine-inverter interaction; magnetizing flux; magnetizing path magnetics; qd induction motor model; rated operating conditions; rotor circuits; rotor leakage saturation; squirrel cage motors; stator leakage saturation; switching frequency phenomena prediction; torque ripple prediction; Distributed computing; Induction machines; Induction motors; Inverters; Magnetic circuits; Magnetic flux; Predictive models; Saturation magnetization; Stators; Torque;
fLanguage
English
Journal_Title
Energy Conversion, IEEE Transactions on
Publisher
ieee
ISSN
0885-8969
Type
jour
DOI
10.1109/TEC.2002.1009469
Filename
1009469
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