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Record W2163764541 · doi:10.1109/ecce.2011.6064009

Integrated magnetic design of small planar transformers for LLC resonant converters

2011· article· en· W2163764541 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInduction Heating and Inverter Technology
Canadian institutionsMemorial University of NewfoundlandSimon Fraser University
FundersMemorial University of NewfoundlandSimon Fraser UniversityEnergy Council of CanadaU.S. Department of Energy
KeywordsParasitic extractionInductanceConvertersTransformerPlanarLeakage inductanceResonant converterElectronic engineeringTransformer typesEngineeringFinite element method500 kHzElectrical engineeringComputer scienceFlyback transformerVoltageStructural engineering

Abstract

fetched live from OpenAlex

Integrating magnetic parasitics in the design of LCC resonant converters provides a solution to reduce parts count and increase power density. This paper provides an efficient design procedure for small planar transformers which integrate transformer leakage inductance and magnetizing inductance into the resonant tank by employing an accurate parasitic prediction model. Finite element simulations were used to create the models using Design of Experiment (DoE) methodology. A planar transformer prototype was designed and tested within a 2.5W LLC resonant converter and results under different operating modes are included to illustrate the resonant behaviour and to validate the presented design procedure.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.912
Threshold uncertainty score0.314

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 head0.055
GPT teacher head0.194
Teacher spread0.139 · 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

Quick stats

Citations12
Published2011
Admission routes2
Has abstractyes

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