View in EDS HTML Full Text PDF Full Text

An Efficient Position Tracking Smoothing Algorithm for Sensorless Operation of Brushless DC Motor Drives.

Saved in:
Bibliographic Details
Title: An Efficient Position Tracking Smoothing Algorithm for Sensorless Operation of Brushless DC Motor Drives.
Authors: Alex, Surya Susan1, Daniel, Asha Elizabeth1
Source: Modelling & Simulation in Engineering. 4/17/2018, p1-9. 9p.
Subjects: Position tracking (Virtual reality), Brushless direct current electric motors, Kalman filtering, Permanent magnets, Thermodynamic state variables
Abstract: This paper presents a new position sensorless scheme in which a smoothing filter algorithm is proposed to improve the results obtained through Extended Kalman Filter (EKF) algorithm in tracking the rotor position for sensorless control of brushless DC motors. The rotor position and speed are estimated from the input voltage and current using the Extended Kalman Filter. States obtained through filtering in each sampling instant are refined, using the new smoothing algorithm, giving much better results. In the proposed method, the estimated state in previous instant is enhanced using the present measurement sample by the smoothing algorithm which is then used to improve the present estimated state variables. The complete system is modelled and simulated in MATLAB to verify the merit of the proposed smoothing algorithm. A comparison with conventional EKF is done for various load torque and speed conditions to establish the performance of the new sensorless algorithm. Simulation results show that the proposed smoothing technique offers better estimation accuracy. The peak error in the estimated speed and rotor position is considerably reduced when compared with EKF. The improved state estimate can be used as feedback for speed control of brushless DC motors in variable speed drives. [ABSTRACT FROM AUTHOR]
Copyright of Modelling & Simulation in Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 129104290
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: An Efficient Position Tracking Smoothing Algorithm for Sensorless Operation of Brushless DC Motor Drives.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Alex%2C+Surya+Susan%22">Alex, Surya Susan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Daniel%2C+Asha+Elizabeth%22">Daniel, Asha Elizabeth</searchLink><relatesTo>1</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Modelling+%26+Simulation+in+Engineering%22">Modelling & Simulation in Engineering</searchLink>. 4/17/2018, p1-9. 9p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Position+tracking+%28Virtual+reality%29%22">Position tracking (Virtual reality)</searchLink><br /><searchLink fieldCode="DE" term="%22Brushless+direct+current+electric+motors%22">Brushless direct current electric motors</searchLink><br /><searchLink fieldCode="DE" term="%22Kalman+filtering%22">Kalman filtering</searchLink><br /><searchLink fieldCode="DE" term="%22Permanent+magnets%22">Permanent magnets</searchLink><br /><searchLink fieldCode="DE" term="%22Thermodynamic+state+variables%22">Thermodynamic state variables</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper presents a new position sensorless scheme in which a smoothing filter algorithm is proposed to improve the results obtained through Extended Kalman Filter (EKF) algorithm in tracking the rotor position for sensorless control of brushless DC motors. The rotor position and speed are estimated from the input voltage and current using the Extended Kalman Filter. States obtained through filtering in each sampling instant are refined, using the new smoothing algorithm, giving much better results. In the proposed method, the estimated state in previous instant is enhanced using the present measurement sample by the smoothing algorithm which is then used to improve the present estimated state variables. The complete system is modelled and simulated in MATLAB to verify the merit of the proposed smoothing algorithm. A comparison with conventional EKF is done for various load torque and speed conditions to establish the performance of the new sensorless algorithm. Simulation results show that the proposed smoothing technique offers better estimation accuracy. The peak error in the estimated speed and rotor position is considerably reduced when compared with EKF. The improved state estimate can be used as feedback for speed control of brushless DC motors in variable speed drives. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Modelling & Simulation in Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=129104290
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1155/2018/4523416
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 9
        StartPage: 1
    Subjects:
      – SubjectFull: Position tracking (Virtual reality)
        Type: general
      – SubjectFull: Brushless direct current electric motors
        Type: general
      – SubjectFull: Kalman filtering
        Type: general
      – SubjectFull: Permanent magnets
        Type: general
      – SubjectFull: Thermodynamic state variables
        Type: general
    Titles:
      – TitleFull: An Efficient Position Tracking Smoothing Algorithm for Sensorless Operation of Brushless DC Motor Drives.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Alex, Surya Susan
      – PersonEntity:
          Name:
            NameFull: Daniel, Asha Elizabeth
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 17
              M: 04
              Text: 4/17/2018
              Type: published
              Y: 2018
          Identifiers:
            – Type: issn-print
              Value: 16875591
          Titles:
            – TitleFull: Modelling & Simulation in Engineering
              Type: main
ResultId 1