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Record W2344859201 · doi:10.1109/tmag.2016.2525007

Equivalent Circuit Modeling of a Hysteresis Interior Permanent Magnet Motor for Electric Submersible Pumps

2016· article· en· W2344859201 on OpenAlexafffund
S. F. Rabbi, M.A. Rahman

Bibliographic record

VenueIEEE Transactions on Magnetics · 2016
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHysteresisRotor (electric)Equivalent circuitMagnetSynchronous motorFinite element methodControl theory (sociology)Magnetic circuitElectric motorAC motorElectronic circuitComputer scienceMaterials scienceElectrical engineeringPhysicsVoltageEngineering

Abstract

fetched live from OpenAlex

This paper presents the magnetic and electrical equivalent circuits of a hysteresis interior permanent magnet (IPM) motor. A hysteresis IPM motor is a solid rotor hybrid synchronous motor combining hysteresis phenomena and permanent excitation in the rotor. When installed in thousands of feet under the sea to drive an electric submersible pump (ESP), it can self-start the ESP without the need of any position sensors, and can improve the efficiency, the performance, and the reliability of the ESP. In this paper, equivalent circuit models are used to predict the transient run-up responses of a 2.5 kW prototype hysteresis IPM motor. Analysis results are compared with 2-D finite-element analysis (FEA) results as well as experimental results. There exists a reasonably close agreement between analytical, FEA, and experimental results, which validates the accuracy of the equivalent circuit models of a hysteresis IPM motor.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.890
Threshold uncertainty score0.733

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 head0.025
GPT teacher head0.218
Teacher spread0.193 · 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 designBench or experimental
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

Citations27
Published2016
Admission routes2
Has abstractyes

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