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Record W2798486368 · doi:10.1109/apec.2018.8341620

Two-phase three-dimension common inductor LLC resonant converter with automatic current sharing

2018· article· en· W2798486368 on OpenAlexaff
Hongliang Wang, Yang Chen, Bo Sheng, Yan‐Fei Liu, P.C. Sen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsInductorCapacitorElectrical impedanceThree-phaseElectronic engineeringHarmonicHarmonic analysisComputer scienceElectrical engineeringEngineeringTopology (electrical circuits)VoltagePhysicsAcoustics

Abstract

fetched live from OpenAlex

Two-phase Three-dimension (3D) common inductor LLC resonant converter is proposed to achieve automatic current sharing. The series inductor of each phase are connected by a Coupled impedance which is inductor, capacitor or short-circuit. A Coupled index is indicated to analyze the current sharing performance under three types converter based on the Fundamental Harmonic Analysis (FHA). The previous method only work at Coupled index equals to 1 and 0, However, the Coupled index can be design any value in (-∞, +∞) for two-phase 3D common inductor LLC converter, and the current sharing performance is better if the Coupled index is designed in negative value. Four steady-state operations under Coupled index is 1, 0.5, 0, -1 are discussed to verify the current sharing improving. A 600W, 12V two-phase LLC converter with short-circuit Coupled impedance prototype is built. The prototype verified the feasibility and demonstrated advantages of the proposed converter..

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.280
Teacher spread0.260 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

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