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Record W2118312366 · doi:10.1109/ias.1993.298882

Self controlled induction motor drive with variable DC link voltage

2002· article· en· W2118312366 on OpenAlexaff
R. Bonert, F.X. Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPulse-width modulationHarmonicsInverterInduction motorControl theory (sociology)VoltageAC motorComputer scienceHarmonicTorquePhysicsElectrical engineeringEngineeringAcoustics

Abstract

fetched live from OpenAlex

A system is proposed in which the voltage of the induction machine is controlled by variation of the DC-link voltage. Using variable DC-link voltage reduces the switching frequency of the inverter and the amplitude of the switched voltage. This reduces the inverter switching losses and the machine losses. Pulse width modulation (PWM) of the inverter is used only to lower the harmonics in motor torque and motor current. This results in a well-defined switching frequency of the inverter is used only to lower the harmonics in motor torque and motor current. This results in a well-defined switching frequency of the inverter and a simple strategy for the harmonic elimination. The PWM is switching only the reduced DC-link voltage, which is proportional to the machine voltage. Simulations show that the self-controlled induction machine with variable DC-link voltage behaves like a voltage controlled DC-machine. The implementation of a drive is described, and experimental results are presented to verify the feasibility of the proposed strategy.>

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.166
Teacher spread0.160 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2002
Admission routes1
Has abstractyes

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