Artificial Neural Based Speed and Flux Estimators for Induction Machine Drives with Matlab/Simulink

Ahmed A. Zaki Diab; Mohammed A. Elsawy; Kotin A. Denis; Salem Alkhalaf; Ziad M. Ali

doi:10.3390/math10081348

Artificial Neural Based Speed and Flux Estimators for Induction Machine Drives with Matlab/Simulink

Ahmed A. Zaki Diab, Mohammed A. Elsawy, Kotin A. Denis, Salem Alkhalaf, Ziad M. Ali

Electrical Engineering

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

In this paper, an Artificial Neural Network (ANN) for accurate estimation of the speed and flux for induction motor (IM) drives has been presented for industrial applications such as electric vehicles (EVs). Two ANN estimators have been designed, one for the rotor speed estimation and the other for the stator and rotor flux estimation. The input training data has been collected based on the currents and voltage data, while the output training data of the speed and stator and rotor fluxes has been established based on the measured speed and flux estimator-based mathematical model of the IM. The designed ANN estimators can overcome the problem of the parameter’s variations and drift integration problems. Matlab/Simulink has been used to develop and test the ANN estimators. The results prove the ANN estimators’ effectiveness under various operation conditions.

Original language	English
Article number	1348
Journal	Mathematics
Volume	10
Issue number	8
DOIs	https://doi.org/10.3390/math10081348
State	Published - 1 Apr 2022

Keywords

artificial neural network
estimation
flux
induction machines drives
speed

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/math10081348

Cite this

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title = "Artificial Neural Based Speed and Flux Estimators for Induction Machine Drives with Matlab/Simulink",

abstract = "In this paper, an Artificial Neural Network (ANN) for accurate estimation of the speed and flux for induction motor (IM) drives has been presented for industrial applications such as electric vehicles (EVs). Two ANN estimators have been designed, one for the rotor speed estimation and the other for the stator and rotor flux estimation. The input training data has been collected based on the currents and voltage data, while the output training data of the speed and stator and rotor fluxes has been established based on the measured speed and flux estimator-based mathematical model of the IM. The designed ANN estimators can overcome the problem of the parameter{\textquoteright}s variations and drift integration problems. Matlab/Simulink has been used to develop and test the ANN estimators. The results prove the ANN estimators{\textquoteright} effectiveness under various operation conditions.",

keywords = "artificial neural network, estimation, flux, induction machines drives, speed",

author = "\{Zaki Diab\}, \{Ahmed A.\} and Elsawy, \{Mohammed A.\} and Denis, \{Kotin A.\} and Salem Alkhalaf and Ali, \{Ziad M.\}",

note = "Publisher Copyright: {\textcopyright} 2022 by the authors. Licensee MDPI, Basel, Switzerland.",

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doi = "10.3390/math10081348",

language = "English",

volume = "10",

journal = "Mathematics",

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T1 - Artificial Neural Based Speed and Flux Estimators for Induction Machine Drives with Matlab/Simulink

AU - Zaki Diab, Ahmed A.

AU - Elsawy, Mohammed A.

AU - Denis, Kotin A.

AU - Alkhalaf, Salem

AU - Ali, Ziad M.

PY - 2022/4/1

Y1 - 2022/4/1

N2 - In this paper, an Artificial Neural Network (ANN) for accurate estimation of the speed and flux for induction motor (IM) drives has been presented for industrial applications such as electric vehicles (EVs). Two ANN estimators have been designed, one for the rotor speed estimation and the other for the stator and rotor flux estimation. The input training data has been collected based on the currents and voltage data, while the output training data of the speed and stator and rotor fluxes has been established based on the measured speed and flux estimator-based mathematical model of the IM. The designed ANN estimators can overcome the problem of the parameter’s variations and drift integration problems. Matlab/Simulink has been used to develop and test the ANN estimators. The results prove the ANN estimators’ effectiveness under various operation conditions.

AB - In this paper, an Artificial Neural Network (ANN) for accurate estimation of the speed and flux for induction motor (IM) drives has been presented for industrial applications such as electric vehicles (EVs). Two ANN estimators have been designed, one for the rotor speed estimation and the other for the stator and rotor flux estimation. The input training data has been collected based on the currents and voltage data, while the output training data of the speed and stator and rotor fluxes has been established based on the measured speed and flux estimator-based mathematical model of the IM. The designed ANN estimators can overcome the problem of the parameter’s variations and drift integration problems. Matlab/Simulink has been used to develop and test the ANN estimators. The results prove the ANN estimators’ effectiveness under various operation conditions.

KW - artificial neural network

KW - estimation

KW - flux

KW - induction machines drives

KW - speed

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Artificial Neural Based Speed and Flux Estimators for Induction Machine Drives with Matlab/Simulink

Abstract

Keywords

UN SDGs

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