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Record W2521527481 · doi:10.11159/eee16.128

Resonant Converter with Fully-Compensated Isolation Transformer

2016· article· en· W2521527481 on OpenAlexvenueno aff
Joon Heo, Seong‐Jeub Jeon

Bibliographic record

VenueProceedings of the World Congress on Electrical Engineering and Computer Systems and Science · 2016
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsnot available
Fundersnot available
KeywordsIsolation transformerTransformerTransformer effectElectrical engineeringForward converterDelta-wye transformerElectronic engineeringComputer scienceDistribution transformerMaterials scienceVoltageBoost converterEngineering

Abstract

fetched live from OpenAlex

In this paper, a resonant converter with a fully-compensated isolation transformer is proposed.An isolation transformer is equipped for the safety of users, and its leakage inductances are used for resonance in a conventional design.In the present proposal, the total self-inductances are used for resonances.When a transformer is fully compensated, its primary voltage is proportional to the secondary current and its secondary voltage to the primary current.This property is useful in a wireless power transfer system, where a constant feeder current is preferable.A constant secondary current is obtained with a constant output voltage of a resonant converter.The proposed resonant converter is applied to a wireless charging system for an electric yard tractor.A prototype charging system of 60 kW is made and tested, and its experimental results are shown.

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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.004
GPT teacher head0.168
Teacher spread0.163 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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