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Record W2735069047 · doi:10.1109/pedg.2017.7972442

Single-phase voltage source inverter with voltage-boosting and power decoupling capabilities

2017· article· en· W2735069047 on OpenAlexaff
Shuang Xu, Riming Shao, Liuchen Chang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsDecoupling (probability)Decoupling capacitorRippleCapacitorInverterVoltageControl theory (sociology)Electrolytic capacitorTopology (electrical circuits)Computer scienceElectronic engineeringEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

This paper proposes a single-phase bridge inverter with both voltage-boosting and power decoupling capabilities. The proposed inverter topology diverts the second-order ripple power into a small film capacitor instead of using a bulky electrolytic capacitor at the DC side, thus eliminating the large electrolytic capacitor that has a short lifetime. The voltage across the decoupling capacitor is controlled as a DC-biased sine wave to cancel out the second-order ripple power, and the redundant energy in decoupling capacitor is used to boost the DC-link voltage, as opposed to being under-utilized in previous DC voltage-reference power decoupling techniques. The proposed topology also maintains the advantages of traditional bridge inverter with unipolar sinusoidal pulse-width modulation technique. Then, the output filter and power decoupling control method are designed for the proposed inverter. Finally, the simulation and experimental results verify the feasibility of the proposed topology and control algorithm, which show successful voltage-boosting and power decoupling.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.888

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)0.0000.000

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 head0.017
GPT teacher head0.226
Teacher spread0.208 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations9
Published2017
Admission routes1
Has abstractyes

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