DocumentCode :
1210223
Title :
Switched reluctance machine model using inverse inductance characterization
Author :
Loop, Benjamin P. ; Sudhoff, Scott D.
Author_Institution :
Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
Volume :
39
Issue :
3
fYear :
2003
Firstpage :
743
Lastpage :
751
Abstract :
This paper sets forth a new switched reluctance machine model based on a current-dependent inverse inductance representation of the flux linkage versus current and position characteristic. This form permits a particularly simple mathematical description. Based on this relationship, a complete state model is derived. The resulting model is easy to implement and computationally efficient. In addition, both manual and genetic-algorithm-based methods of parameter identification are set forth. The accuracy of the model is tested via comparison to laboratory measurements of the machine´s steady-state voltage and current waveforms as well as torque-speed characteristics. The proposed model is shown to be quite accurate.
Keywords :
genetic algorithms; inductance; machine theory; magnetic flux; parameter estimation; reluctance motors; torque; complete state model; current characteristic; current-dependent inverse inductance; flux linkage; genetic-algorithm-based methods; inverse inductance characterization; parameter identification; position characteristic; reluctance motors; steady-state current waveforms; steady-state voltage waveforms; switched reluctance machine model; torque-speed characteristics; Couplings; Current measurement; Inductance; Inverse problems; Laboratories; Parameter estimation; Reluctance machines; Steady-state; Testing; Torque measurement;
fLanguage :
English
Journal_Title :
Industry Applications, IEEE Transactions on
Publisher :
ieee
ISSN :
0093-9994
Type :
jour
DOI :
10.1109/TIA.2003.811785
Filename :
1201542
Link To Document :
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