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Record W3004911649 · doi:10.1109/tpel.2020.2971424

Planar Transformers in LLC Resonant Converters: High-Frequency Fringing Losses Modeling

2020· article· en· W3004911649 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

VenueIEEE Transactions on Power Electronics · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConvertersTransformerInductancePlanarTopology (electrical circuits)Electrical engineeringComputer scienceElectronic engineeringEngineeringVoltage

Abstract

fetched live from OpenAlex

Fringing losses play a detrimental role in high-frequency transformers. The tendency toward higher power density and miniaturization of power converters leads to higher switching frequency and enforces the use of low-profile components such as gapped planar transformers. Due to the air gap, lower magnetizing inductance and better regulation of LLC (L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sub> , L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> , C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> ) can be achieved, but fringing fluxes can also be induced, resulting in extra magnetic losses and more hotspots. These losses are highly dependent on the frequency and the core material, so it is critical to model them for gapped planar transformers in LLC resonant converters, which operate at high frequencies and use ferrite material. In this article, fringing losses for gapped ferrite transformers in LLC converters are thoroughly modeled in order to provide a precise prediction regardless of the materials and core geometries. The proposed method provides an accurate and compact formula for predicting the fringing losses of planar transformers. This formula is obtained based on the finite-element method so as to consider and evaluate different design parameters. An LLC resonant converter with different planar transformers is implemented to show the compatibility of the proposed model. Experimental results show the higher accuracy of the proposed model compared to traditional ones and confirm that the proposed loss model can be applied to diverse core shapes. In addition, the gradient descent method is used to calibrate the theoretical and experimental results. Moreover, temperature deviations of the transformer due to the fringing losses are measured and evaluated both experimentally and theoretically to show the accuracy of the proposed loss formula. Due to the proposed model's higher accuracy, an improved design procedure for planar transformers is obtained, adding substantial value for design engineers.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.202
Teacher spread0.192 · 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