Model predictive direct flux vector control of multi three-phase induction motor drives

A model predictive control scheme for multiphase induction machines, configured as multi three-phase structures, is proposed in this paper. The predictive algorithm uses a Direct Flux Vector Control scheme based on a multi three-phase approach, where each three-phase winding set is independently con...

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Main Authors: Rubino, Sandro, Bojoi, Radu, Odhano, Shafiq Ahmed, Zanchetta, Pericle
Format: Article
Language:English
Published: IEEE 2018
Online Access:https://eprints.nottingham.ac.uk/53426/
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author Rubino, Sandro
Bojoi, Radu
Odhano, Shafiq Ahmed
Zanchetta, Pericle
author_facet Rubino, Sandro
Bojoi, Radu
Odhano, Shafiq Ahmed
Zanchetta, Pericle
author_sort Rubino, Sandro
building Nottingham Research Data Repository
collection Online Access
description A model predictive control scheme for multiphase induction machines, configured as multi three-phase structures, is proposed in this paper. The predictive algorithm uses a Direct Flux Vector Control scheme based on a multi three-phase approach, where each three-phase winding set is independently controlled. In this way, the fault tolerant behavior of the drive system is improved. The proposed solution has been tested with a multi-modular power converter feeding a six-phase asymmetrical induction machine (10kW, 6000 rpm). Complete details about the predictive control scheme and adopted flux observer are included. The experimental validation in both generation and motoring mode is reported, including open-winding post-fault operations. The experimental results demonstrate full drive controllability, including deep flux-weakening operation.
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spelling nottingham-534262018-08-23T08:51:36Z https://eprints.nottingham.ac.uk/53426/ Model predictive direct flux vector control of multi three-phase induction motor drives Rubino, Sandro Bojoi, Radu Odhano, Shafiq Ahmed Zanchetta, Pericle A model predictive control scheme for multiphase induction machines, configured as multi three-phase structures, is proposed in this paper. The predictive algorithm uses a Direct Flux Vector Control scheme based on a multi three-phase approach, where each three-phase winding set is independently controlled. In this way, the fault tolerant behavior of the drive system is improved. The proposed solution has been tested with a multi-modular power converter feeding a six-phase asymmetrical induction machine (10kW, 6000 rpm). Complete details about the predictive control scheme and adopted flux observer are included. The experimental validation in both generation and motoring mode is reported, including open-winding post-fault operations. The experimental results demonstrate full drive controllability, including deep flux-weakening operation. IEEE 2018-08-23 Article PeerReviewed application/pdf en https://eprints.nottingham.ac.uk/53426/1/Model%20Predictive%20Direct%20Flux%20Vector%20Control%20of.pdf Rubino, Sandro, Bojoi, Radu, Odhano, Shafiq Ahmed and Zanchetta, Pericle (2018) Model predictive direct flux vector control of multi three-phase induction motor drives. IEEE Transactions on Industry Applications . p. 1. ISSN 0093-9994 http://dx.doi.org/10.1109/TIA.2018.2829458 doi:10.1109/TIA.2018.2829458 doi:10.1109/TIA.2018.2829458
spellingShingle Rubino, Sandro
Bojoi, Radu
Odhano, Shafiq Ahmed
Zanchetta, Pericle
Model predictive direct flux vector control of multi three-phase induction motor drives
title Model predictive direct flux vector control of multi three-phase induction motor drives
title_full Model predictive direct flux vector control of multi three-phase induction motor drives
title_fullStr Model predictive direct flux vector control of multi three-phase induction motor drives
title_full_unstemmed Model predictive direct flux vector control of multi three-phase induction motor drives
title_short Model predictive direct flux vector control of multi three-phase induction motor drives
title_sort model predictive direct flux vector control of multi three-phase induction motor drives
url https://eprints.nottingham.ac.uk/53426/
https://eprints.nottingham.ac.uk/53426/
https://eprints.nottingham.ac.uk/53426/