A method to improve flux estimation under Gaussian noise in sensorless stator flux control of induction motors

Jong Kwang Kim, Yong Keun Lee, Jang Wook Lee

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

Abstract

This paper proposes a programmable Low Pass Filter (LPF) to improve the performance of sensorless stator flux orientation control for induction motors. Commonly, a pure integrator based on the voltage model is used to estimate stator flux linkages for its simplicity. However, due to noise errors such as strong Gaussian noise variance, a drift and a dc offset are easily produced by the integrator when the back electromotive force (emf) is relatively smaller than Gaussian noise variance. Thus, the pure integrator is replaced by the programmable LPF to reduce those errors. The performance of the induction motor control mainly depends on the accuracy of the estimated flux. When the back emf is very small and noisy, an enhanced method of the programmable LPF is applied to improve the flux estimation. Such method is verified and implemented by a simulation tool called Simulink.

Original languageEnglish
Title of host publicationIEACon 2016 - 2016 IEEE Industrial Electronics and Applications Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages179-184
Number of pages6
ISBN (Electronic)9781509009251
DOIs
StatePublished - 12 Oct 2017
Event2016 IEEE Industrial Electronics and Applications Conference, IEACon 2016 - Kota Kinabalu, Sabah, Malaysia
Duration: 20 Nov 201622 Nov 2016

Publication series

NameIEACon 2016 - 2016 IEEE Industrial Electronics and Applications Conference

Conference

Conference2016 IEEE Industrial Electronics and Applications Conference, IEACon 2016
Country/TerritoryMalaysia
CityKota Kinabalu, Sabah
Period20/11/1622/11/16

Keywords

  • Back emf
  • DC offset
  • drift
  • flux estimation
  • noise
  • programmable LPF

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