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Record W2948682603 · doi:10.1109/tpel.2019.2920810

Using Multilevel ZVZCS Converters to Improve Light-Load Efficiency in Low Power Applications

2019· article· en· W2948682603 on OpenAlexafffund
Javad Khodabakhsh, Ramtin Rasoulinezhad, Gerry Moschopoulos

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConvertersElectronic engineeringVoltagePower (physics)CapacitorMaterials scienceComputer scienceElectrical engineeringControl theory (sociology)EngineeringPhysics

Abstract

fetched live from OpenAlex

In this letter, the use of three-level (TL), zero-voltage-zero-current switching (ZVZCS) converters is investigated as a way of improving light-load efficiency in full-bridge converters with mosfets. The general operation of an example TL-ZVZCS full-bridge converter is briefly explained and the basic principles as to how it can how improve light-load efficiency are discussed. Experimental results that compare the efficiency of a prototype of the example TL-ZVZCS converter to that of the conventional zero voltage switching (ZVS)-pulsewidth modulation full-bridge are presented to confirm the superior light-load efficiency of TL-ZVZCS converters.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.927
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.005
GPT teacher head0.227
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.

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

Citations10
Published2019
Admission routes2
Has abstractyes

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