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Record W4312897625 · doi:10.1109/tpel.2022.3223050

Novel Resonant Power Feedback DC-DC Converter

2022· article· en· W4312897625 on OpenAlexaff
Snehal Bagawade, Majid Pahlevani, Praveen Jain

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsBoost converterTopology (electrical circuits)Forward converterIntegrating ADCBuck–boost converterElectronic engineeringFlyback converterBuck converterSINADRVoltageControl theory (sociology)Electrical engineeringEngineeringComputer science

Abstract

fetched live from OpenAlex

In this article, a novel soft-switched isolated dc–dc converter topology is proposed that consists of a main power converter using a standard topology, augmented with a resonant power feedback circuit. The power feedback circuit utilizes a fraction of the output power to regulate the input voltage of the main converter. Input voltage regulation proves to be advantageous in applications where wide range of source voltage variations are experienced, such as in photovoltaic microinverters. The operation of main converter with a regulated input voltage results in a near-constant phase-shift angle and a high-frequency current wave shape with a low root mean square value over the entire range of operating conditions. Moreover, the operation with near constant phase-shift angle and the presence of additional resonant current in the feedback circuit extend the range of soft-switched operation of semiconductor devices in the converter. The proposed converter topology and its theoretical analysis is verified through an experimental prototype.

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 score0.011

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 integrity0.0000.000
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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Power ElectronicsSame topicAdvanced DC-DC ConvertersFrench-language works237,207