<div class="csl-bib-body">
<div class="csl-entry">Janisch, G., Kugi, A., & Kemmetmüller, W. (2022). Model calibration strategy for energy-efficient operation of induction machines. In A. Kugi, A. Körner, W. Kemmetmüller, A. Deutschmann-Olek, F. Breitenecker, & I. Troch (Eds.), <i>10th Vienna International Conference on Mathematical Modelling MATHMOD 2022: Vienna Austria, 27–29 July 2022</i> (pp. 307–312). https://doi.org/10.1016/j.ifacol.2022.09.113</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/81209
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dc.description.abstract
This contribution describes a novel calibration procedure for nonlinear induction machine models. It is based on measurements of the electrical quantities and the rotational speed, and uses additional measurements of the torque. Since the method uses quasi steady-state measurements, the calculations required for the model calibration can be performed with low computational costs in the frequency domain. Compared to the scientific state of the art, higher harmonics are taken into account in addition to the fundamental wave. The main goal of the parametrized model is to accurately capture the behavior of the induction machine in the vicinity of maximum efficiency operating points. Thus, the calibration strategy is tailored to these important operating points and allows to obtain a very high accuracy with a rather simple model. The proposed calibration procedure is verified by measurements on a test bench. It is shown that a high model accuracy can be achieved with the calibrated model.
en
dc.language.iso
en
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dc.relation.ispartofseries
IFAC-PapersOnLine
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dc.subject
induction machine
en
dc.subject
parameter identification
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dc.subject
magnetic saturation
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dc.subject
energy-efficient control
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dc.subject
loss minimizing operation
en
dc.title
Model calibration strategy for energy-efficient operation of induction machines
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.relation.issn
2405-8963
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dc.description.startpage
307
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dc.description.endpage
312
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
10th Vienna International Conference on Mathematical Modelling MATHMOD 2022: Vienna Austria, 27–29 July 2022