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Record W2294668914 · doi:10.1109/tpel.2015.2499194

A Multimode 1-MHz PFC Front End With Digital Peak Current Modulation

2015· article· en· W2294668914 on OpenAlexafffund
Ryan Fernandes, Olivier Trescases

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTotal harmonic distortionInductorPower factorControl theory (sociology)Rectifier (neural networks)Electrical engineeringVoltageElectronic engineeringEngineeringPhysicsComputer science

Abstract

fetched live from OpenAlex

This work presents a novel mixed-signal control scheme for a boost power factor correction (PFC) rectifier. The digital controller modulates the inductor peak current to produce a low-distortion ac line current in discontinuous conduction mode (DCM) and continuous conduction mode (CCM), without the need for average current sensing. A lookup table (LUT) optimizes efficiency at low input currents, by allowing operation at 125-500-kHz DCM based on calculated thresholds. At high input currents, the converter operates at 1-MHz CCM for reduced inductor footprint. An analog off-time generator with a digital frequency locked loop facilitates CCM operation, eliminating the need for slope compensation in the current loop and reduces frequency variations. The LUT is programmed with an adaptive output voltage of 250/450 V for low/high mains line voltage (85-265 Vrms) to optimize efficiency over a broad range of conditions. The 150-W PFC prototype operates up to 1 MHz with a peak efficiency of 95% and a total harmonic distortion of 5%.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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 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

Citations25
Published2015
Admission routes2
Has abstractyes

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