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Record W2169378674 · doi:10.1109/tie.2007.899877

A Practical Copper Loss Measurement Method for the Planar Transformer in High-Frequency Switching Converters

2007· article· en· W2169378674 on OpenAlexaff
Yongtao Han, Wilson Eberle, Yan‐Fei Liu

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2007
Typearticle
Languageen
FieldEngineering
TopicSilicon Carbide Semiconductor Technologies
Canadian institutionsQueen's University
Fundersnot available
KeywordsCopper lossTransformerEnergy efficient transformerElectromagnetic coilElectronic engineeringConvertersLinear variable differential transformerRotary variable differential transformerDistribution transformerPlanarEngineeringElectrical engineeringMaterials scienceComputer scienceVoltage

Abstract

fetched live from OpenAlex

In this paper, a new and practical measurement method is proposed to characterize the planar transformer copper loss operating in a high-frequency switching mode power supply (SMPS). The scheme is easy to set up, and it provides an equivalent winding alternating current resistance, which is the result of all the field effects on the transformer windings to achieve more accurate copper loss characterization. A detailed error analysis for the proposed copper loss measurement method is conducted. The analysis results can provide useful guidelines on the SMPS transformer copper loss measurement scheme design. Measurement results on the copper loss of a planar transformer in a high-frequency dc/dc converter are presented. In order to verify the measurement results, a time-domain finite-element analysis transient solver is adopted to analyze the transformer copper loss. Good matching between the simulation and measurement results is achieved.

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)0.001
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.061
GPT teacher head0.298
Teacher spread0.237 · 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
GenreMethods

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

Citations52
Published2007
Admission routes1
Has abstractyes

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