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Record W2947391973 · doi:10.1109/apec.2019.8721926

High-Step-Up Boost Converter Based on Coupled Inductor, Voltage Lift and Clamp Cells

2019· article· en· W2947391973 on OpenAlexaff
G. A. K. Somiruwan, L. H. P. N. Gunawardena, Dulika Nayanasiri, Yunwei Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInductorConvertersInductanceLeakage inductanceVoltageWaveformBoost converterElectronic engineeringLift (data mining)ClamperClampLeakage (economics)Electrical engineeringComputer scienceEngineeringMaterials scienceMechanical engineeringClamping

Abstract

fetched live from OpenAlex

A high-step-up boost converter based on a coupled-inductor, a voltage lift and a clamp cells is proposed in this paper. The energy stored in the leakage inductances of the coupled inductor is recycled using the voltage lift and the clamp cells to obtain the higher gain. The operation of the proposed converter is explained using ideal waveforms. The effect of leakage inductance is considered in the analysis in addition to the non-ideal behaviour of the semiconductor devices. The operation of the power converter is validated and verified using the simulation and the experimental results. The performance improvements obtained using the proposed solution is compared against the existing converters.

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 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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
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 integrity0.0000.000
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 head0.004
GPT teacher head0.179
Teacher spread0.174 · 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; both teacher heads agree on what is shown here.

Study designSimulation or modeling
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

Citations7
Published2019
Admission routes1
Has abstractyes

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