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Record W1927154264 · doi:10.1109/pesc.2004.1355567

A large signal dynamic model for single-phase AC-to-DC converters with power factor correction

2004· article· en· W1927154264 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

Venue2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551) · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsDuty cyclePulse-width modulationConvertersWaveformControl theory (sociology)Small-signal modelDC biasPower factorPower (physics)SIGNAL (programming language)VoltageComputer scienceElectronic engineeringEngineeringPhysicsElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

This paper presents a model for average current control that can be applied to DC-to-DC converters and AC-to- DC power factor correction (PFC) circuits. The proposed DC-to-DC model consists of two parts: 1) an averaged DC-to-DC converter topology with all the switching elements replaced by dependent sources 2) an average current control scheme with a pulse width modulation (PWM) model, which determines the duty cycles. Similarly, the AC-to-DC PFC model is obtained by combining an averaged boost converter model with the PFC control scheme using average current control. To verify the proposed model, simulated results were compared to experimental waveforms. The experimental results demonstrate that the model can correctly predict the steady-state and large signal dynamic behavior for average current controlled DC-to-DC and AC-to-DC PFC converters.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.836
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.250
Teacher spread0.239 · 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