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Fuzzy MRAS Speed Sensorless Induction Motor Drive Control for Electric Vehicles.

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Title: Fuzzy MRAS Speed Sensorless Induction Motor Drive Control for Electric Vehicles.
Authors: Rind, Saqib Jamshed1 (AUTHOR) sjrind@neduet.edu.pk, Javed, Saba2 (AUTHOR), Khan, Hashim Raza2,3 (AUTHOR), Khalid, Muhammad Hashir Bin3,4 (AUTHOR), Arshad, Kamran4,5 (AUTHOR), Assaleh, Khaled1,4,5 (AUTHOR)
Source: Energies (19961073). Mar2026, Vol. 19 Issue 6, p1580. 28p.
Subject Terms: *Sensorless control systems, *Electric vehicles, *Fuzzy logic, *Robust control, *Induction motors, *Adaptive control systems
Abstract: This paper proposes a new fuzzy logic-based rotor flux model reference adaptive system (FLC-MRAS) for rotor speed estimation in induction motor drives, replacing the constant-gain PI controller used in conventional MRAS schemes. The proposed observer simultaneously incorporates both rotor flux and electromagnetic torque errors to enhance estimation accuracy and robustness against load torque disturbances. A nonlinear Mamdani-type fuzzy logic controller (FLC) with two inputs and one output, employing triangular membership functions and seven fuzzy sets, is adopted. The effectiveness and useful operational performance of the proposed approach is examined through extensive simulation cases under various vehicle speed driving profiles and load torque conditions using an indirect vector-controlled induction motor drive. In order to investigate the effective operational performance of a speed estimator, different cases are prepared according to the vehicle requirements. To examine the robustness of the proposed observer under realistic operating conditions, rotor resistance variation is incorporated into the simulation framework. This approach allows assessment of MRAS performance under practical nonlinearities and parameter uncertainties encountered in real applications. Comparative results demonstrate superior speed regulation and speed tracking, reduced estimation error, and faster convergence of the adaptive tuning signal for better speed estimation compared to the PI-MRAS observer. The proposed scheme provides the suitable choice of traction drive adoption for electric vehicle (EV) applications. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 192592754
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Fuzzy MRAS Speed Sensorless Induction Motor Drive Control for Electric Vehicles.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Rind%2C+Saqib+Jamshed%22">Rind, Saqib Jamshed</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> sjrind@neduet.edu.pk</i><br /><searchLink fieldCode="AR" term="%22Javed%2C+Saba%22">Javed, Saba</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Khan%2C+Hashim+Raza%22">Khan, Hashim Raza</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Khalid%2C+Muhammad+Hashir+Bin%22">Khalid, Muhammad Hashir Bin</searchLink><relatesTo>3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Arshad%2C+Kamran%22">Arshad, Kamran</searchLink><relatesTo>4,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Assaleh%2C+Khaled%22">Assaleh, Khaled</searchLink><relatesTo>1,4,5</relatesTo> (AUTHOR)
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  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Mar2026, Vol. 19 Issue 6, p1580. 28p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Sensorless+control+systems%22">Sensorless control systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Electric+vehicles%22">Electric vehicles</searchLink><br />*<searchLink fieldCode="DE" term="%22Fuzzy+logic%22">Fuzzy logic</searchLink><br />*<searchLink fieldCode="DE" term="%22Robust+control%22">Robust control</searchLink><br />*<searchLink fieldCode="DE" term="%22Induction+motors%22">Induction motors</searchLink><br />*<searchLink fieldCode="DE" term="%22Adaptive+control+systems%22">Adaptive control systems</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper proposes a new fuzzy logic-based rotor flux model reference adaptive system (FLC-MRAS) for rotor speed estimation in induction motor drives, replacing the constant-gain PI controller used in conventional MRAS schemes. The proposed observer simultaneously incorporates both rotor flux and electromagnetic torque errors to enhance estimation accuracy and robustness against load torque disturbances. A nonlinear Mamdani-type fuzzy logic controller (FLC) with two inputs and one output, employing triangular membership functions and seven fuzzy sets, is adopted. The effectiveness and useful operational performance of the proposed approach is examined through extensive simulation cases under various vehicle speed driving profiles and load torque conditions using an indirect vector-controlled induction motor drive. In order to investigate the effective operational performance of a speed estimator, different cases are prepared according to the vehicle requirements. To examine the robustness of the proposed observer under realistic operating conditions, rotor resistance variation is incorporated into the simulation framework. This approach allows assessment of MRAS performance under practical nonlinearities and parameter uncertainties encountered in real applications. Comparative results demonstrate superior speed regulation and speed tracking, reduced estimation error, and faster convergence of the adaptive tuning signal for better speed estimation compared to the PI-MRAS observer. The proposed scheme provides the suitable choice of traction drive adoption for electric vehicle (EV) applications. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.3390/en19061580
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 28
        StartPage: 1580
    Subjects:
      – SubjectFull: Sensorless control systems
        Type: general
      – SubjectFull: Electric vehicles
        Type: general
      – SubjectFull: Fuzzy logic
        Type: general
      – SubjectFull: Robust control
        Type: general
      – SubjectFull: Induction motors
        Type: general
      – SubjectFull: Adaptive control systems
        Type: general
    Titles:
      – TitleFull: Fuzzy MRAS Speed Sensorless Induction Motor Drive Control for Electric Vehicles.
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            NameFull: Rind, Saqib Jamshed
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            NameFull: Javed, Saba
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            NameFull: Khan, Hashim Raza
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            NameFull: Khalid, Muhammad Hashir Bin
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            NameFull: Arshad, Kamran
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            – D: 15
              M: 03
              Text: Mar2026
              Type: published
              Y: 2026
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              Value: 19
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            – TitleFull: Energies (19961073)
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