MétaCan
Menu
Back to cohort
Record W2807855001 · doi:10.1109/tie.2018.2844855

Current-Fed Isolated LCC-T Resonant Converter With ZCS and Improved Transformer Utilization

2018· article· en· W2807855001 on OpenAlex
Venkata R. Vakacharla, Akshay Kumar Rathore

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.

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsConcordia University
Fundersnot available
KeywordsTransformerInductorConvertersElectrical engineeringCapacitive sensingElectronic engineeringFlyback transformerDelta-wye transformerEnergy efficient transformerVoltageResonant converterCurrent transformerEngineering

Abstract

fetched live from OpenAlex

Resonant converters with capacitive output filters are quite popular for their higher voltage gain and compact designs. But the majority of the converters underutilize the transformer as they are subjected to discontinuous currents. This discontinuous current possesses huge current ripples that produce huge core losses and aggravate the temperature rise of the transformer. This often leads to saturation of the transformer. This paper presents an LCC-T resonant dc-dc converter with a capacitive output filter operating all switches in the zero current switching (ZCS) switching mode and whose transformer current is a continuous sinusoidal with minimum stress on resonant tank components. This is achieved by bringing the transformer in series to a resonant inductor. The proposed converter is simulated in power simulation (PSIM) 11.0.1. A proof-of-concept model rated 288 W is designed and developed, and hardware results are presented as verification to theory.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
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
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.240
Teacher spread0.216 · 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