Fuzzy logic enhanced direct torque control with space vector modulation
Over the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux co...
Saved in:
Main Authors: | , , , , |
---|---|
Other Authors: | |
Format: | Article |
Published: |
Institute of Advanced Engineering and Science
2023
|
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.uniten.dspace-23740 |
---|---|
record_format |
dspace |
spelling |
my.uniten.dspace-237402023-05-29T14:51:25Z Fuzzy logic enhanced direct torque control with space vector modulation Tan J.-D. Koh S.-P. Tiong S.-K. Ali K. Abdalla A. 38863172300 22951210700 15128307800 36130958600 56050971600 Over the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux controllers, a fuzzy logic control method is implemented in the proposed modification to achieve a more constant switching frequency while minimizing the torque error. The fuzzy logic controller controls the voltages in direct and quadratic reference frame (Vd, Vq). This approach fully utilizes the switching capability of the inverter and thus improving the overall system performance. To overcome issues in open loop stator flux such as DC drift and saturation, a closed loop estimation method of stator flux is also proposed based on voltage model and low pass filter. The performance of the proposed control strategy is benchmarked with that of a conventional DTC� SVM. Simulations and experiments were carried out and the results show that the proposed method outperforms the conventional DTC-SVM in terms of DC-offset elimination and overall system robustness. � 2018 Institute of Advanced Engineering and Science. All rights reserved. Final 2023-05-29T06:51:25Z 2023-05-29T06:51:25Z 2018 Article 10.11591/ijeecs.v11.i2.pp704-710 2-s2.0-85048181272 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048181272&doi=10.11591%2fijeecs.v11.i2.pp704-710&partnerID=40&md5=0dbafb43e782d30349e6a31a31ef9839 https://irepository.uniten.edu.my/handle/123456789/23740 11 2 704 710 All Open Access, Hybrid Gold, Green Institute of Advanced Engineering and Science Scopus |
institution |
Universiti Tenaga Nasional |
building |
UNITEN Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Tenaga Nasional |
content_source |
UNITEN Institutional Repository |
url_provider |
http://dspace.uniten.edu.my/ |
description |
Over the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux controllers, a fuzzy logic control method is implemented in the proposed modification to achieve a more constant switching frequency while minimizing the torque error. The fuzzy logic controller controls the voltages in direct and quadratic reference frame (Vd, Vq). This approach fully utilizes the switching capability of the inverter and thus improving the overall system performance. To overcome issues in open loop stator flux such as DC drift and saturation, a closed loop estimation method of stator flux is also proposed based on voltage model and low pass filter. The performance of the proposed control strategy is benchmarked with that of a conventional DTC� SVM. Simulations and experiments were carried out and the results show that the proposed method outperforms the conventional DTC-SVM in terms of DC-offset elimination and overall system robustness. � 2018 Institute of Advanced Engineering and Science. All rights reserved. |
author2 |
38863172300 |
author_facet |
38863172300 Tan J.-D. Koh S.-P. Tiong S.-K. Ali K. Abdalla A. |
format |
Article |
author |
Tan J.-D. Koh S.-P. Tiong S.-K. Ali K. Abdalla A. |
spellingShingle |
Tan J.-D. Koh S.-P. Tiong S.-K. Ali K. Abdalla A. Fuzzy logic enhanced direct torque control with space vector modulation |
author_sort |
Tan J.-D. |
title |
Fuzzy logic enhanced direct torque control with space vector modulation |
title_short |
Fuzzy logic enhanced direct torque control with space vector modulation |
title_full |
Fuzzy logic enhanced direct torque control with space vector modulation |
title_fullStr |
Fuzzy logic enhanced direct torque control with space vector modulation |
title_full_unstemmed |
Fuzzy logic enhanced direct torque control with space vector modulation |
title_sort |
fuzzy logic enhanced direct torque control with space vector modulation |
publisher |
Institute of Advanced Engineering and Science |
publishDate |
2023 |
_version_ |
1806428292219142144 |
score |
13.214268 |