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An Extended-Speed Low-Ripple Torque Control of Switched Reluctance Motor Drives

2014· article· en· 275 citations· W4250907637 on OpenAlex· 10.1109/tpel.2014.2316272

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

Full frame distilled prediction

Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

Candidate categories
Meta-epidemiology (narrow)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Bench or experimentalConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: none
Teacher disagreement score
0.886
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Opus teacher head0.003
GPT teacher head0.200
Teacher spread
0.197 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

In this paper, an extended-speed low-ripple torque control of switched reluctance motor (SRM) drives using torque sharing function (TSF) is proposed. Two operational modes are defined for the online TSF during commutation: In Mode I, absolute value of rate of change of flux linkage (ARCFL) of incoming phase is higher than outgoing phase; in Mode II, ARCFL of outgoing phase is higher than incoming phase. In order to compensate the torque error produced by imperfect tracking of phase current, a proportional and integral compensator with torque error is added to the torque reference of outgoing phase in Mode I and incoming phase in Mode II. Therefore, the total torque is determined by the phase with lower ARCFL rather than the phase with higher ARCFL as in conventional TSFs. The maximum torque-ripple-free speed of the proposed TSF is increased to more than ten times as the best case in conventional TSFs. Finally, the proposed TSF is verified by both simulations and experiments with a 2.3 kW, 6000 rpm, three-phase 12/8 SRM operating in both linear magnetic and saturated magnetic regions. Results show that the proposed TSF has higher average torque, and much lower torque ripples compared to conventional TSFs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

The record

Venue
IEEE Transactions on Power Electronics
Topic
Electric Motor Design and Analysis
Field
Engineering
Canadian institutions
McMaster University
Funders
Canada Research Chairs
Keywords
Switched reluctance motorControl theory (sociology)Torque limiterDirect torque controlTorque rippleTorqueStall torqueDamping torqueReluctance motorTorque motorPhase (matter)PhysicsEngineeringComputer scienceVoltageInduction motorElectrical engineeringControl (management)
Has abstract in OpenAlex
yes