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Model-based flux weakening strategy for synchronous machines without additional regulators
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0001-6831-3474
ABB Oy, Finland.
2018 (English)In: IET Electric Power Applications, ISSN 1751-8660, E-ISSN 1751-8679, Vol. 12, no 9, p. 1283-1290Article in journal (Refereed) Published
Abstract [en]

This study proposes a model-based control strategy for flux weakening operation of a synchronous reluctance machine, with a methodology that is extendible to any synchronous machine. The strategy leverages in the presence of digital non-linear models that describe the relation between currents and flux linkages in the machine. Such models are usually needed for conventional maximum-torque-per-ampere control and sensorless control, but here they are exploited to achieve flux-weakening operation without the need of flux weakening regulators, ensuring a seamless transition between the operating regions of the machine. The external voltage regulation loop for flux weakening is thus eliminated and substituted by a combination of look-up tables and binary searches, which are executed within one digital control period and which generate the required current and voltage references that fulfil the drive limitations. The method can also be coupled with mechanisms to compensate for magnetic parameter inaccuracies, to achieve an accurate tracking of the reference torque. The proposed solution is simulated and validated in a laboratory test bench on an 11 kW synchronous reluctance machine.

Place, publisher, year, edition, pages
Institution of Engineering and Technology, 2018. Vol. 12, no 9, p. 1283-1290
Keywords [en]
digital control, machine control, magnetic flux, reluctance machines, synchronous motor drives, torque control, voltage control
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-251655DOI: 10.1049/iet-epa.2018.0065ISI: 000450294800007Scopus ID: 2-s2.0-85056227382OAI: oai:DiVA.org:kth-251655DiVA, id: diva2:1316319
Note

QC 20190528

Available from: 2019-05-17 Created: 2019-05-17 Last updated: 2019-05-28

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Citation style
  • apa
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