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Record W4282832479 · doi:10.3390/en15124319

A Trans-Inverse Magnetic Coupling Single-Phase AC-AC Converter

2022· article· en· W4282832479 on OpenAlexaff
S. Esmaeili, kasra Ghobadi, Hassan Zare, Mohsin Jamil, Ashraf Ali Khan, Amin Mahmoudi

Bibliographic record

VenueEnergies · 2022
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVoltage sourceSnubberInductorTransformerBuck–boost converterBuck converterElectronic engineeringHarmonicsForward converterVoltageEngineeringElectrical engineeringBoost converterControl theory (sociology)Computer scienceCapacitor

Abstract

fetched live from OpenAlex

This paper introduces a new single-phase AC-AC converter based on an impedance source circuit. Like the existing single-phase impedance source AC-AC converters, it has the buck-boost ability and direct ac conversion. The input and output voltage possesses the same ground, and the phase angle is maintained and reversed smoothly. The presented converter utilizes a coupled transformer which allows the designer to exploit the transformer’s turns ratio as a variable to attain the desired output voltage. Additionally, the used transformer provides an option to obtain higher voltage gain by decreasing the turns ratio. Hence, smaller size of the coupled inductors is required for the higher voltage cases. To eliminate the switching voltage and current spikes on the power switches, a safe commutation strategy is used instead of utilizing snubber circuits. Furthermore, the input current is continuous and sinusoidal with low harmonics thanks to embedding the input inductor in series with the input source. Additionally, a dynamic voltage restorer is presented based on the proposed converter to compensate the voltage sag and swell faults. Simulation results are provided to evaluate the theoretical analysis. Finally, a laboratory prototype has been fabricated to demonstrate the validation of the presented 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 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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
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)0.0030.000

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 head0.017
GPT teacher head0.211
Teacher spread0.194 · 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 teacher head, not a consensus.

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

Citations4
Published2022
Admission routes1
Has abstractyes

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