Loading…

PWM-Based Predictive Direct Torque Control of Switched Reluctance Machine for Accurate Torque Tracking With Minimization of Phase RMS Currents

This paper proposes a novel PWM-based optimal predictive torque controller for Switched Reluctance Machines (SRMs). The highly non-linear characteristics of flux-linkage and phase torque present challenges in achieving real-time optimal torque control in SRMs. In this work, a cost function, encompas...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on industry applications 2024-09, Vol.60 (5), p.6899-6912
Main Authors: Thirumalasetty, Mouli, Narayanan, G.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c264t-6d918702c9889a2d7db037eb48f4d562234077890cb3a51495841bb3d1d589ea3
cites cdi_FETCH-LOGICAL-c264t-6d918702c9889a2d7db037eb48f4d562234077890cb3a51495841bb3d1d589ea3
container_end_page 6912
container_issue 5
container_start_page 6899
container_title IEEE transactions on industry applications
container_volume 60
creator Thirumalasetty, Mouli
Narayanan, G.
description This paper proposes a novel PWM-based optimal predictive torque controller for Switched Reluctance Machines (SRMs). The highly non-linear characteristics of flux-linkage and phase torque present challenges in achieving real-time optimal torque control in SRMs. In this work, a cost function, encompassing the instantaneous torque error and the RMS values of phase currents is formulated to be minimized. An analytical expression for the optimal duty ratio towards this objective is derived resulting in improved computational efficiency. The performance of the proposed torque controller is compared with two state-of-the-art finite control set predictive torque controllers through extensive simulations and experiments. The tests are conducted at various operating torque and speed levels on a 4-phase, 8/6 pole SRM. Results demonstrate that the proposed controller delivers better torque tracing performance in terms of lower average and RMS torque errors than the existing techniques. Also the proposed method results in higher torque per ampere, lower sound pressure levels (SPL emission), and lower computational time. The proposed controller tracks the torque accurately even in the presence of −20% to +20% modeling errors.
doi_str_mv 10.1109/TIA.2024.3400174
format article
fullrecord <record><control><sourceid>crossref_ieee_</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TIA_2024_3400174</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>10529624</ieee_id><sourcerecordid>10_1109_TIA_2024_3400174</sourcerecordid><originalsourceid>FETCH-LOGICAL-c264t-6d918702c9889a2d7db037eb48f4d562234077890cb3a51495841bb3d1d589ea3</originalsourceid><addsrcrecordid>eNpNkMlOwzAURS0EEqWwZ8HCP5DiKYOXJUyVGlG1QV1Gjv1CDCUBxwHBR_DNpGqRWL3NuffqHYTOKZlQSuRlPptOGGFiwgUhNBYHaEQll4HkUXyIRoRIHkgpxTE66brnAREhFSP0s1hnwZXqwOCFA2O1tx-Ar60D7XHeuvcecNo23rUb3FZ49Wm9rgd4CZtee9VowJnStW0AV63DU617pzz8RXOn9IttnvDa-hpntrGv9lt52zbbtkU9DONltsJp7xw0vjtFR5XadHC2v2P0eHuTp_fB_OFulk7ngWaR8EFkJE1iwrRMEqmYiU1JeAylSCphwoixQUIcJ5LokqvhTxkmgpYlN9SEiQTFx4jserVru85BVbw5-6rcV0FJsfVZDD6Lrc9i73OIXOwiFgD-4SGTERP8F_JRcl8</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>PWM-Based Predictive Direct Torque Control of Switched Reluctance Machine for Accurate Torque Tracking With Minimization of Phase RMS Currents</title><source>IEEE Electronic Library (IEL) Journals</source><creator>Thirumalasetty, Mouli ; Narayanan, G.</creator><creatorcontrib>Thirumalasetty, Mouli ; Narayanan, G.</creatorcontrib><description>This paper proposes a novel PWM-based optimal predictive torque controller for Switched Reluctance Machines (SRMs). The highly non-linear characteristics of flux-linkage and phase torque present challenges in achieving real-time optimal torque control in SRMs. In this work, a cost function, encompassing the instantaneous torque error and the RMS values of phase currents is formulated to be minimized. An analytical expression for the optimal duty ratio towards this objective is derived resulting in improved computational efficiency. The performance of the proposed torque controller is compared with two state-of-the-art finite control set predictive torque controllers through extensive simulations and experiments. The tests are conducted at various operating torque and speed levels on a 4-phase, 8/6 pole SRM. Results demonstrate that the proposed controller delivers better torque tracing performance in terms of lower average and RMS torque errors than the existing techniques. Also the proposed method results in higher torque per ampere, lower sound pressure levels (SPL emission), and lower computational time. The proposed controller tracks the torque accurately even in the presence of −20% to +20% modeling errors.</description><identifier>ISSN: 0093-9994</identifier><identifier>EISSN: 1939-9367</identifier><identifier>DOI: 10.1109/TIA.2024.3400174</identifier><identifier>CODEN: ITIACR</identifier><language>eng</language><publisher>IEEE</publisher><subject>Computational modeling ; Control systems ; Inductance ; optimal control ; Predictive control ; pulse width modulation ; Reluctance machines ; Switches ; Torque ; Torque control ; torque ripple</subject><ispartof>IEEE transactions on industry applications, 2024-09, Vol.60 (5), p.6899-6912</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c264t-6d918702c9889a2d7db037eb48f4d562234077890cb3a51495841bb3d1d589ea3</citedby><cites>FETCH-LOGICAL-c264t-6d918702c9889a2d7db037eb48f4d562234077890cb3a51495841bb3d1d589ea3</cites><orcidid>0000-0001-9663-9383 ; 0000-0002-9968-761X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10529624$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids></links><search><creatorcontrib>Thirumalasetty, Mouli</creatorcontrib><creatorcontrib>Narayanan, G.</creatorcontrib><title>PWM-Based Predictive Direct Torque Control of Switched Reluctance Machine for Accurate Torque Tracking With Minimization of Phase RMS Currents</title><title>IEEE transactions on industry applications</title><addtitle>TIA</addtitle><description>This paper proposes a novel PWM-based optimal predictive torque controller for Switched Reluctance Machines (SRMs). The highly non-linear characteristics of flux-linkage and phase torque present challenges in achieving real-time optimal torque control in SRMs. In this work, a cost function, encompassing the instantaneous torque error and the RMS values of phase currents is formulated to be minimized. An analytical expression for the optimal duty ratio towards this objective is derived resulting in improved computational efficiency. The performance of the proposed torque controller is compared with two state-of-the-art finite control set predictive torque controllers through extensive simulations and experiments. The tests are conducted at various operating torque and speed levels on a 4-phase, 8/6 pole SRM. Results demonstrate that the proposed controller delivers better torque tracing performance in terms of lower average and RMS torque errors than the existing techniques. Also the proposed method results in higher torque per ampere, lower sound pressure levels (SPL emission), and lower computational time. The proposed controller tracks the torque accurately even in the presence of −20% to +20% modeling errors.</description><subject>Computational modeling</subject><subject>Control systems</subject><subject>Inductance</subject><subject>optimal control</subject><subject>Predictive control</subject><subject>pulse width modulation</subject><subject>Reluctance machines</subject><subject>Switches</subject><subject>Torque</subject><subject>Torque control</subject><subject>torque ripple</subject><issn>0093-9994</issn><issn>1939-9367</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNpNkMlOwzAURS0EEqWwZ8HCP5DiKYOXJUyVGlG1QV1Gjv1CDCUBxwHBR_DNpGqRWL3NuffqHYTOKZlQSuRlPptOGGFiwgUhNBYHaEQll4HkUXyIRoRIHkgpxTE66brnAREhFSP0s1hnwZXqwOCFA2O1tx-Ar60D7XHeuvcecNo23rUb3FZ49Wm9rgd4CZtee9VowJnStW0AV63DU617pzz8RXOn9IttnvDa-hpntrGv9lt52zbbtkU9DONltsJp7xw0vjtFR5XadHC2v2P0eHuTp_fB_OFulk7ngWaR8EFkJE1iwrRMEqmYiU1JeAylSCphwoixQUIcJ5LokqvhTxkmgpYlN9SEiQTFx4jserVru85BVbw5-6rcV0FJsfVZDD6Lrc9i73OIXOwiFgD-4SGTERP8F_JRcl8</recordid><startdate>20240901</startdate><enddate>20240901</enddate><creator>Thirumalasetty, Mouli</creator><creator>Narayanan, G.</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0001-9663-9383</orcidid><orcidid>https://orcid.org/0000-0002-9968-761X</orcidid></search><sort><creationdate>20240901</creationdate><title>PWM-Based Predictive Direct Torque Control of Switched Reluctance Machine for Accurate Torque Tracking With Minimization of Phase RMS Currents</title><author>Thirumalasetty, Mouli ; Narayanan, G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c264t-6d918702c9889a2d7db037eb48f4d562234077890cb3a51495841bb3d1d589ea3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Computational modeling</topic><topic>Control systems</topic><topic>Inductance</topic><topic>optimal control</topic><topic>Predictive control</topic><topic>pulse width modulation</topic><topic>Reluctance machines</topic><topic>Switches</topic><topic>Torque</topic><topic>Torque control</topic><topic>torque ripple</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Thirumalasetty, Mouli</creatorcontrib><creatorcontrib>Narayanan, G.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) Online</collection><collection>IEEE</collection><collection>CrossRef</collection><jtitle>IEEE transactions on industry applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Thirumalasetty, Mouli</au><au>Narayanan, G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>PWM-Based Predictive Direct Torque Control of Switched Reluctance Machine for Accurate Torque Tracking With Minimization of Phase RMS Currents</atitle><jtitle>IEEE transactions on industry applications</jtitle><stitle>TIA</stitle><date>2024-09-01</date><risdate>2024</risdate><volume>60</volume><issue>5</issue><spage>6899</spage><epage>6912</epage><pages>6899-6912</pages><issn>0093-9994</issn><eissn>1939-9367</eissn><coden>ITIACR</coden><abstract>This paper proposes a novel PWM-based optimal predictive torque controller for Switched Reluctance Machines (SRMs). The highly non-linear characteristics of flux-linkage and phase torque present challenges in achieving real-time optimal torque control in SRMs. In this work, a cost function, encompassing the instantaneous torque error and the RMS values of phase currents is formulated to be minimized. An analytical expression for the optimal duty ratio towards this objective is derived resulting in improved computational efficiency. The performance of the proposed torque controller is compared with two state-of-the-art finite control set predictive torque controllers through extensive simulations and experiments. The tests are conducted at various operating torque and speed levels on a 4-phase, 8/6 pole SRM. Results demonstrate that the proposed controller delivers better torque tracing performance in terms of lower average and RMS torque errors than the existing techniques. Also the proposed method results in higher torque per ampere, lower sound pressure levels (SPL emission), and lower computational time. The proposed controller tracks the torque accurately even in the presence of −20% to +20% modeling errors.</abstract><pub>IEEE</pub><doi>10.1109/TIA.2024.3400174</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-9663-9383</orcidid><orcidid>https://orcid.org/0000-0002-9968-761X</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0093-9994
ispartof IEEE transactions on industry applications, 2024-09, Vol.60 (5), p.6899-6912
issn 0093-9994
1939-9367
language eng
recordid cdi_crossref_primary_10_1109_TIA_2024_3400174
source IEEE Electronic Library (IEL) Journals
subjects Computational modeling
Control systems
Inductance
optimal control
Predictive control
pulse width modulation
Reluctance machines
Switches
Torque
Torque control
torque ripple
title PWM-Based Predictive Direct Torque Control of Switched Reluctance Machine for Accurate Torque Tracking With Minimization of Phase RMS Currents
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T23%3A26%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=PWM-Based%20Predictive%20Direct%20Torque%20Control%20of%20Switched%20Reluctance%20Machine%20for%20Accurate%20Torque%20Tracking%20With%20Minimization%20of%20Phase%20RMS%20Currents&rft.jtitle=IEEE%20transactions%20on%20industry%20applications&rft.au=Thirumalasetty,%20Mouli&rft.date=2024-09-01&rft.volume=60&rft.issue=5&rft.spage=6899&rft.epage=6912&rft.pages=6899-6912&rft.issn=0093-9994&rft.eissn=1939-9367&rft.coden=ITIACR&rft_id=info:doi/10.1109/TIA.2024.3400174&rft_dat=%3Ccrossref_ieee_%3E10_1109_TIA_2024_3400174%3C/crossref_ieee_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c264t-6d918702c9889a2d7db037eb48f4d562234077890cb3a51495841bb3d1d589ea3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=10529624&rfr_iscdi=true