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High-Precision Parameter Identification of High-Speed Magnetic Suspension Motor
- Source :
- IEEE Transactions on Energy Conversion. 33:20-31
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- This paper presents an elaborate scheme, which is different from the traditional parameter identification method, to estimate the parameters precisely for high-speed magnetic suspension motor. It is well known that the inductance and resistance of each winding play an important role in ensuring the stability of the controller for motor. There have been sufficient research works on equivalent circuit model, where the input and output data are assumed to be true value, and unknown circuit parameters are obtained by solving the equivalent circuit equations of motor. However, the output data are often interfered with noises, such as measurement error, the high-frequency components from pulse width modulation signals and sampling errors. The system response output data are reconstructed through applying in stochastic theory, which is different from the traditional filter techniques, to eliminate effectively the above-mentioned noises. Thus, the parameters can be estimated precisely. As an experimental verification, parameters estimated by the proposed method are applied in calculation of switching point between pulse width modulation mode and pulse amplitude modulation mode for magnetic suspension motor. The experimental results validate the effectiveness of the proposed method.
- Subjects :
- Electric motor
0209 industrial biotechnology
Computer science
020208 electrical & electronic engineering
Energy Engineering and Power Technology
02 engineering and technology
AC motor
Inductance
020901 industrial engineering & automation
Pulse-amplitude modulation
Control theory
0202 electrical engineering, electronic engineering, information engineering
Equivalent circuit
Electrical and Electronic Engineering
Synchronous motor
Pulse-width modulation
Induction motor
Subjects
Details
- ISSN :
- 15580059 and 08858969
- Volume :
- 33
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Energy Conversion
- Accession number :
- edsair.doi...........1b3fc775fb5f9e59db45e90e40c47a45