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Record W2104728950 · doi:10.1109/tpel.2011.2171370

Buck Converter With Merged Active Charge-Controlled Capacitive Attenuation

2011· article· en· W2104728950 on OpenAlexaff
Aleksandar Radić, Aleksandar Prodić

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInductorCapacitorCapacitive sensingBuck converterAttenuator (electronics)Transient responseSlew rateControl theory (sociology)Electronic engineeringDigital controlVoltageElectrical engineeringAttenuationComputer scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

This letter introduces a converter and a complementary digital controller that, compared to conventional buck, have a smaller output filter volume, improved dynamic response, and lower switching losses. To reduce the volume and switching losses, the input-to-output voltage difference is decreased with a capacitive attenuator that replaces the input filter capacitor and has approximately the same volume. Both the attenuator and the downstream buck converter share the same set of switches, minimizing conduction losses. A single digital controller governs operation of the both stages. The controller utilizes the inductor current to regulate the center tap voltage, through a charge-control algorithm. During transients, the attenuator is bypassed, so the inductor current slew rate is improved. Experiments with a 5-1.5-V, 2.5-A, 1-MHz prototype show that, compared to the conventional buck, the merged topology has 43% smaller inductor, 36% smaller output capacitor, up to 30% lower power losses, and a 25% 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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.190
Teacher spread0.181 · 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

Citations28
Published2011
Admission routes1
Has abstractyes

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