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Record W2106657459 · doi:10.1109/apec.2012.6165953

Digitally controlled multi-phase buck-converter with merged capacitive attenuator

2012· article· en· W2106657459 on OpenAlexaff
Behzad Mahdavikhah, Parth Jain, Aleksandar Prodić

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCapacitorInductorBuck converterCapacitive sensingConvertersBuck–boost converterVoltageReduction (mathematics)Electronic engineeringMaterials scienceCapacitanceComputer scienceElectrical engineeringEngineeringPhysicsMathematics

Abstract

fetched live from OpenAlex

This paper introduces a new topology that combines a capacitive divider and an interleaved buck to reduce the volume of multi-phase step-down converters. The size reduction is obtained with a low penalty in conduction losses, input filter size, and controller complexity. At heavy loads, the converter efficiency is comparable to that of a conventional buck and at light to medium loads it is improved. The volume reduction is obtained by utilizing the inductors of the buck stage to regulate the tap voltages of the capacitive divider. This eliminates a bulky energy transfer capacitor existing in other switch capacitor (SC) circuits, reduces the number of switches in the conduction path, and simplifies control of the converter. Experimental results obtained with a 7V-to-1V, 10A, 1 MHz prototype demonstrate that the merged capacitor converter has 15% smaller inductor, 13% reduction in output capacitor value and up to 35% reduction in power losses, and 15% faster transient response than a time-optimal controlled buck.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.878
Threshold uncertainty score0.921

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 communication0.0000.001
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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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

Citations18
Published2012
Admission routes1
Has abstractyes

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