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Record W2117909678 · doi:10.1109/apec.2010.5433616

ZVS and ZCS dc-dc PWM full-bridge fuel cell converters

2010· article· en· W2117909678 on OpenAlexafffund
Ahmad Mousavi, Pritam Das, Gerry Moschopoulos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsWestern University
FundersNational Research Council CanadaNational Science Council
KeywordsConvertersPulse-width modulationBoost converterVoltageĆuk converterForward converterHalf bridgeComputer scienceElectronic engineeringElectrical engineeringCapacitorEngineering

Abstract

fetched live from OpenAlex

PWM current-fed full-bridge dc-dc boost converters are typically in applications where the output voltage is considerably higher than the input voltage, such as fuel cell converters. The zero-voltage switching (ZVS) active-clamp converter is the most commonly used converter of this type. Zero-current switching (ZCS) techniques have also been used in current-fed full bridge converters, but not in fuel cell converters. In the paper, a comparison is made between the ZVS active-clamp full-bridge converter and a ZCS full-bridge converter. The operation of the two converters is discussed in detail and experimental results obtained from each converter are presented and compared.

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: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.926

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)0.0000.000

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 head0.005
GPT teacher head0.190
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; 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

Citations9
Published2010
Admission routes2
Has abstractyes

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