Sensorless Loss Model Control of the Six-Phase Induction Motor in All Speed Range by Extended Kalman Filter
This paper proposes a simple extended Kalman filter (EKF) loss model controller (LMC) for efficiency improvement of a six-phase induction machine in all speed ranges. The proposed method is fast and can be operated online. If the machine parameters are changed during the operation, the EKF algorithm...
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doaj-162b75e218304d1bb6e5ff1e27bcdfe42021-03-30T01:54:03ZengIEEEIEEE Access2169-35362020-01-01811874111875010.1109/ACCESS.2020.29648288952611Sensorless Loss Model Control of the Six-Phase Induction Motor in All Speed Range by Extended Kalman FilterAsghar Taheri0https://orcid.org/0000-0001-8266-3075Hai-Peng Ren1https://orcid.org/0000-0003-3834-5103Mohammad Hosein Holakooie2https://orcid.org/0000-0002-8656-0986School of Electronics and Information Engineering, Xi’an Technological University, Xi’an, ChinaSchool of Electronics and Information Engineering, Xi’an Technological University, Xi’an, ChinaElectrical Engineering Department, University of Zanjan, Zanjan, IranThis paper proposes a simple extended Kalman filter (EKF) loss model controller (LMC) for efficiency improvement of a six-phase induction machine in all speed ranges. The proposed method is fast and can be operated online. If the machine parameters are changed during the operation, the EKF algorithm is activated to find the parameters to ensure optimal efficiency operation. Not only is the motor speed measurement difficult at low speeds but it is also difficult to calculate the machine efficiency at the same speeds. Thus, the EKF model can estimate speed, load, and motor efficiency at low speed ranges so that optimization can be done in all loads and speed ranges. Unlike the conventional LMC method, the proposed method is independent of parameter variations. Because of the independency of this method against the parameter variations, it works similarly to the search based efficiency control methods. Two DSP boards including estimator and controller are used to achieve high accuracy and speed in estimating and controlling machines. The simulation and experimental results verify the robustness of the sensorless method against parameter variations.https://ieeexplore.ieee.org/document/8952611/EKFsix-phase induction motorFOCloss model control |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Asghar Taheri Hai-Peng Ren Mohammad Hosein Holakooie |
spellingShingle |
Asghar Taheri Hai-Peng Ren Mohammad Hosein Holakooie Sensorless Loss Model Control of the Six-Phase Induction Motor in All Speed Range by Extended Kalman Filter IEEE Access EKF six-phase induction motor FOC loss model control |
author_facet |
Asghar Taheri Hai-Peng Ren Mohammad Hosein Holakooie |
author_sort |
Asghar Taheri |
title |
Sensorless Loss Model Control of the Six-Phase Induction Motor in All Speed Range by Extended Kalman Filter |
title_short |
Sensorless Loss Model Control of the Six-Phase Induction Motor in All Speed Range by Extended Kalman Filter |
title_full |
Sensorless Loss Model Control of the Six-Phase Induction Motor in All Speed Range by Extended Kalman Filter |
title_fullStr |
Sensorless Loss Model Control of the Six-Phase Induction Motor in All Speed Range by Extended Kalman Filter |
title_full_unstemmed |
Sensorless Loss Model Control of the Six-Phase Induction Motor in All Speed Range by Extended Kalman Filter |
title_sort |
sensorless loss model control of the six-phase induction motor in all speed range by extended kalman filter |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
This paper proposes a simple extended Kalman filter (EKF) loss model controller (LMC) for efficiency improvement of a six-phase induction machine in all speed ranges. The proposed method is fast and can be operated online. If the machine parameters are changed during the operation, the EKF algorithm is activated to find the parameters to ensure optimal efficiency operation. Not only is the motor speed measurement difficult at low speeds but it is also difficult to calculate the machine efficiency at the same speeds. Thus, the EKF model can estimate speed, load, and motor efficiency at low speed ranges so that optimization can be done in all loads and speed ranges. Unlike the conventional LMC method, the proposed method is independent of parameter variations. Because of the independency of this method against the parameter variations, it works similarly to the search based efficiency control methods. Two DSP boards including estimator and controller are used to achieve high accuracy and speed in estimating and controlling machines. The simulation and experimental results verify the robustness of the sensorless method against parameter variations. |
topic |
EKF six-phase induction motor FOC loss model control |
url |
https://ieeexplore.ieee.org/document/8952611/ |
work_keys_str_mv |
AT asghartaheri sensorlesslossmodelcontrolofthesixphaseinductionmotorinallspeedrangebyextendedkalmanfilter AT haipengren sensorlesslossmodelcontrolofthesixphaseinductionmotorinallspeedrangebyextendedkalmanfilter AT mohammadhoseinholakooie sensorlesslossmodelcontrolofthesixphaseinductionmotorinallspeedrangebyextendedkalmanfilter |
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1724186186602250240 |