DocumentCode :
725617
Title :
A reduced-order model based induction machine self-commissioning method
Author :
Hao Ge ; Jing Guo ; Bilgin, Berker ; Ye Jin ; Loukanov, Voiko ; Emadi, Ali
Author_Institution :
Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, ON, Canada
fYear :
2015
fDate :
14-17 June 2015
Firstpage :
1
Lastpage :
8
Abstract :
A new method which uses the voltage source PWM inverter (VSI) to identify the induction machine (IM) parameters is proposed based on the reduced-order models of induction machine. All the variables for parameter extraction are obtained by the inverter and converted to the dq frame using the FOC software modules. The variables are DC values and low-pass filter may be used to reduce the harmonic and noise effects. The least-square and curve fitting methods are employed to remove the nonlinear effects. The proposed method provides high accuracy for induction machine parameter characterization and can be used to measure the saturated magnetizing inductance as a function of frequency and magnetizing current. It can be integrated with the FOC software as the self-commissioning function without much cost of additional software.
Keywords :
PWM invertors; asynchronous machines; curve fitting; harmonics suppression; least squares approximations; low-pass filters; reduced order systems; FOC software module; IM; VSI; curve fitting method; dq frame; harmonic reduction; least square method; low-pass filter; magnetizing current; nonlinear effect removal; reduced-order model based induction machine self-commissioning method; voltage source PWM inverter; Decision support systems; Frequency measurement; Inverters; Pulse width modulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transportation Electrification Conference and Expo (ITEC), 2015 IEEE
Conference_Location :
Dearborn, MI
Type :
conf
DOI :
10.1109/ITEC.2015.7165740
Filename :
7165740
Link To Document :
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