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Record W2614277927 · doi:10.1109/apec.2017.7931008

Low-volume hybrid tap-connected SC-buck converter with shared output capacitor

2017· article· en· W2614277927 on OpenAlexaff
Timothy McRae, Nenad Vukadinovic, Aleksandar Prodić

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBuck converterInductorCapacitorTopology (electrical circuits)Buck–boost converterSwitched capacitorElectronic engineeringĆuk converterVoltageMaterials scienceComputer scienceElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

This paper introduces a hybrid converter topology for low-power applications that uses a novel connection of a switched capacitor (SC) converter and a buck converter to achieve smaller volume and better power processing efficiency than conventional step-down solutions. Specific advantages of this topology include smaller inductor volume, reduced input filter requirements, and lower voltages stress of the semiconductor components. These advantages are achieved by connecting the buck converter to a tap of a 2:1 ladder SC circuit and both stages share the middle capacitor of the capacitor stack. A direct connection of the stacked input capacitors of the SC to the source acts as a portion of the input filter and reduces the voltage swing across the inductor and switching components, allowing for smaller inductance value and lower voltage stress. The advantages of this topology are verified with a digitally controlled 24 V to 5 V/ 5 A, 1 MHz experimental prototype having about 50% smaller inductor, and about 30% lower voltage stress than a conventional buck converter.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
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 communication0.0000.001
Open science0.0010.000
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 head0.009
GPT teacher head0.194
Teacher spread0.185 · 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; both teacher heads agree on what is shown here.

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

Citations9
Published2017
Admission routes1
Has abstractyes

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