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Record W2972059151 · doi:10.1109/tia.2019.2939517

Two-Converter-Based Frequency-Sharing Operation and Control of a Brushless Doubly Fed Reluctance Motor Drive

2019· article· en· W2972059151 on OpenAlexaff
Ronald S. Rebeiro, Andrew M. Knight

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2019
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsStatorConvertersElectromagnetic coilSwitched reluctance motorRotor (electric)Control theory (sociology)Magnetic reluctancePower (physics)EngineeringAC motorReluctance motorAutomatic frequency controlInduction motorTorqueMachine controlControl engineeringComputer scienceControl (management)Electrical engineeringElectric motorVoltagePhysicsMagnet

Abstract

fetched live from OpenAlex

This article investigates a novel two-converter-based operation of a brushless doubly fed reluctance machine (BDFRM). The BDFRM has a ducted rotor, and the stator is wound with two distributed windings, which are fed from two separate power converters. Operation theory with frequency sharing between the two windings is introduced. The prototype BDFRM design, machine assembly, and the corresponding motor drive implementation processes are discussed. The control strategy for frequency sharing mode of operation with two variable winding frequencies is discussed. Subsequently, the BDFRM drive is tested in frequency sharing mode at varying speed levels and loads.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.851
Threshold uncertainty score0.720

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)

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.

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

Opus teacher head0.009
GPT teacher head0.219
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2019
Admission routes1
Has abstractyes

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