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Identification of PM synchronous machines in the frequency domain by broadband excitation

Book Contribution - Book Chapter Conference Contribution

Modelling and sidentification of synchronous machines has attracted much attention during the past decades. Although the standstill frequency response (SSFR) method has become standardized (IEEE Std. 115) it has some disadvantages (e.g. it is a time consuming method). To overcome these, the use of broadband excitation has been proposed in the literature. In this paper the use of broadband excitation for the frequency domain identification of permanent magnet synchronous machines is investigated. The measurment set-up and method are discussed, special attention is given to the selection of the applied excitation signals. Three broadband signals suitable for frequency domain parameter identification are discussed and compared in measurements. The obtained frequency domain data can be used in different applications, examples are given in this paper. Furthermore the extraction of a parameteric model from the nonparemteric frequency domain data is briefly discussed. The identified parameters can be used to study the influence of staturation or can be applied in hte simulation and control of permanent magnet synchronous machiens. Measurement results demonstrate that boradband frequency domain identification can be applied to extract the parameters (inductances) of permanent magnet synchronous machines. Moreover, the reproducibility of the method is shown to be good as the variation in the paremters obtained in different measurment sessions is low. Future work on the subject will include a closer investigation of the variations in the obtained parameters, the use of higher order models and the application of more complex estimation algorithms.
Book: 19th International Symposium on Power Electronics, Electrical drives, automation and motion
Publication year:2008
Keywords:SSFR, permanent magnet synchronous machine, parameter identification, frequency domain methods
  • ORCID: /0000-0002-8654-8397/work/92287326
  • Scopus Id: 51849132629