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Record W2111309068 · doi:10.1109/tpel.2013.2273939

An Interleaved LLC Resonant Converter Operating at Constant Switching Frequency

2013· article· en· W2111309068 on OpenAlexaff
Zhiyuan Hu, Yajie Qiu, Laili Wang, Yan‐Fei Liu

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsInterleavingConvertersRippleCapacitorSwitching frequencyPower (physics)Electrical engineeringInductorConstant (computer programming)Electronic engineeringEngineeringVoltageComputer scienceControl theory (sociology)PhysicsControl (management)

Abstract

fetched live from OpenAlex

The interleaving technique is necessary for LLC resonant converters to achieve high power level. The advantages include expanded power capacity, lower output ripple current, and higher light-load efficiency by using phase shedding. However, conventional frequency-controlled LLC converters will lose regulation in individual phases if all the phases are operating at the same switching frequency, causing load sharing problem. Existing load sharing solutions for interleaved LLC converters all have limitations. In this paper, a switch-controlled capacitor (SCC) modulated LLC converter (SCC-LLC) is presented to solve the load-sharing problem. With constant switching frequency, interleaving and phase shedding can be achieved. A 600-W, two-phase interleaved constant frequency SCC-LLC prototype is built to verify the feasibility and demonstrate the advantages.

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 score0.002
Threshold uncertainty score0.006

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.210
Teacher spread0.204 · 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

Citations223
Published2013
Admission routes1
Has abstractyes

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