DocumentCode :
1337747
Title :
Improving the accuracy of the rotor resistance estimate for vector-controlled induction machines
Author :
Wade, S. ; Dunnigan, M.W. ; Williams, B.W.
Author_Institution :
Dept. of Comput. & Electr. Eng., Heriot-Watt Univ., Edinburgh, UK
Volume :
144
Issue :
5
fYear :
1997
fDate :
9/1/1997 12:00:00 AM
Firstpage :
285
Lastpage :
294
Abstract :
The estimation of rotor resistance in a vector-controlled induction machine is necessary to achieve high performance torque control. The extended Kalman filter (EKF) or the extended Luenberger observer (ELO) have been used to estimate this machine parameter. Three techniques are presented for use with the EKF and ELO which improve the accuracy of the rotor resistance estimate, either in both estimators, or in the EKF alone. These techniques are: the use of the synchronous two-axis (de-qe) frame model of the induction machine with the EKF, the inclusion of the core loss resistance to precalculate the phase currents used by the estimators, and the injection of a high frequency sine wave on the flux current reference command. These improvements are achieved without increasing the complexity of the estimation algorithms. The consequent improvements in the rotor resistance estimation are illustrated through simulation and practical implementation of a vector-controlled induction machine. A high performance digital signal processor (DSP) is used in the practical implementation
Keywords :
Kalman filters; digital signal processing chips; electric resistance; induction motors; losses; machine control; machine theory; magnetic flux; observers; parameter estimation; rotors; torque control; DSP; core loss resistance; extended Kalman filter; extended Luenberger observer; flux current reference command; high frequency sine wave injection; high performance digital signal processor; high performance torque control; machine parameter estimation; phase currents precalculation; rotor resistance estimate; synchronous two-axis frame model; vector-controlled induction machines;
fLanguage :
English
Journal_Title :
Electric Power Applications, IEE Proceedings -
Publisher :
iet
ISSN :
1350-2352
Type :
jour
DOI :
10.1049/ip-epa:19971133
Filename :
660220
Link To Document :
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