Sensorless self-commissioning of synchronous reluctance motors at standstill

Marko Hinkkanen, Paolo Pescetto, Eemeli Mölsä, Seppo E. Saarakkala, Gianmario Pellegrino, Radu Bojoi

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

5 Citations (Scopus)
149 Downloads (Pure)

Abstract

This paper proposes a standstill method for identification of the magnetic model of synchronous reluctance motors (SyRMs). The saturation and cross-saturation effects are properly taken into account. The motor is fed by an inverter with a short sequence of bipolar voltage pulses that are first applied on the rotor d- and q-axes separately and then simultaneously on both the axes. The stator flux linkages are computed by integrating the induced voltages. Using the current and flux samples, the parameters of an algebraic magnetic model are estimated by means of linear least squares. The proposed method is robust against the stator resistance variations and inverter nonlinearities due to the high test voltages (of the order of the rated voltage). The fitted model matches very well with the reference saturation characteristics, measured using a constant-speed method, and enables extrapolation outside the sample range. The method was tested with a 2.2-kW SyRM, whose shaft was uncoupled from any mechanical load, which is the most demanding condition for this method. The proposed method can be used for automatic self-commissioning of sensorless SyRM drives at standstill.

Original languageEnglish
Title of host publicationProceedings of the 2016 International Conference on Electrical Machines, ICEM 2016
PublisherIEEE
Pages1174-1180
Number of pages7
ISBN (Electronic)9781509025381
DOIs
Publication statusPublished - 4 Sep 2016
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Electrical Machines - Lausanne, Switzerland
Duration: 4 Sep 20167 Sep 2016
Conference number: 22
http://www.icem.cc/2016/

Conference

ConferenceInternational Conference on Electrical Machines
Abbreviated titleICEM
CountrySwitzerland
CityLausanne
Period04/09/201607/09/2016
Internet address

Keywords

  • Flux maps
  • identification
  • linear least squares (LLS)
  • saturation characteristics

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