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Record W2110200019 · doi:10.1109/ccece.1997.608384

Sensorless permanent magnet synchronous motor drives

2002· article· en· W2110200019 on OpenAlex

Why this work is in the frame

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

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRotor (electric)StatorVoltageSynchronous motorPosition (finance)Control theory (sociology)Position sensorComputer scienceInverterMagnetAC motorMotor drivePermanent magnet synchronous motorControl engineeringEngineeringElectrical engineeringMechanical engineeringArtificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

Permanent magnet (PM) synchronous motors are gaining wide recognition over other types of motors in drive systems, mainly due to their inherently advantageous features. For successful operation of PM motor drives, position and speed sensing are of critical importance. Due to the drawbacks of conventional sensors the speed and position sensorless PM motor drive draws wide attention. In this paper, an algorithm is developed which enables the PM motor drive to operate successfully at any speed without any mechanical speed and position sensors, while keeping the maximum output voltage of the inverter constant. New expressions have been derived for the rotor speed and position in terms of stator voltages and currents. A method has been suggested to calculate the input voltage of the motor. The present work is also an attempt to provide a brief review of speed and position sensorless PM drives with simulation and experimental results.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.873
Threshold uncertainty score1.000

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)0.0030.001

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 head0.007
GPT teacher head0.174
Teacher spread0.167 · 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

Quick stats

Citations6
Published2002
Admission routes1
Has abstractyes

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