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Record W2868708300 · doi:10.1109/63.974384

Optimization of switching frequencies in the limited-pool random space vector PWM strategy for inverter-fed drives

2001· article· en· W2868708300 on OpenAlexaff
A.M. Trzynadlowski, Michael Møller Bech, Frede Blaabjerg, J.K. Pedersen, R.L. Kirlin, M. Zigliotto

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2001
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPulse-width modulationInverterEMIControl theory (sociology)Switching frequencyInterval (graph theory)Modulation (music)Space vector modulationSampling (signal processing)Computer scienceElectronic engineeringElectromagnetic interferenceMathematicsEngineeringVoltagePhysicsElectrical engineeringAcousticsFilter (signal processing)Control (management)

Abstract

fetched live from OpenAlex

A space vector PWM technique for inverter fed AC drives which, in contrast with known random modulation methods, is characterized by a very small pool of randomly used switching frequencies, is presented. The limited size of the pool facilitates design of digitally implemented subsystems of the drive, whose settings depend on the length of sampling interval. A method for optimal selection of pool frequencies is described and validated by experimental evidence, including EMI measurements.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score0.734

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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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

Citations44
Published2001
Admission routes1
Has abstractyes

Explore more

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