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Record W2014827685 · doi:10.1109/apec.2014.6803573

Low-volume stackable flyback converter with near minimum deviation controller

2014· article· en· W2014827685 on OpenAlexaff
Aleksandar Radić, Adrian Straka, Aleksandar Prodić

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFlyback transformerFlyback converterBuck converterBuck–boost converterCapacitorFlyback diodeVoltageElectronic engineeringController (irrigation)Computer scienceControl theory (sociology)InductorMaterials scienceElectrical engineeringBoost converterEngineering

Abstract

fetched live from OpenAlex

This paper introduces a flyback-based low-volume modular converter and complementary mixed-signal controller that provide input voltage and output current sharing as well as near optimal transient response. This serial-input paralleloutput switch-mode power supply (SMPS) is well suited for high-step down ratio applications where, compared to a conventionally used multi-phase buck, it requires a smaller output filter volume, lower MOSFET blocking voltages, and provides better dynamic response. The stackable flyback also has better power processing efficiency and provides inherent passive current sharing. These advantages are achieved by utilizing low-voltage flyback cells and a novel implementation of minimum deviation control method. Experiments with a 12-to-1-V, 4-A, 500kHz 2-cell stacked flyback converter prototype show that, compared to an equivalent 12-V 2-phase conventional buck with approximately the same inductor volume, the introduced converter has 14% smaller output capacitor, up to 40% lower power losses, and 33% faster transient response.

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 categoriesInsufficient payload (model declined to judge)
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 score0.945
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)0.0010.001

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 head0.003
GPT teacher head0.167
Teacher spread0.164 · 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.

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

Citations13
Published2014
Admission routes1
Has abstractyes

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