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Record W4317038633 · doi:10.1109/tie.2023.3236119

Modified Transformerless Series-Connected Current Source Converter Without Series-Connected Switches

2023· article· en· W4317038633 on OpenAlexaff
Ling Xing, Qiang Wei, Yunwei Li

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2023
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsLakehead UniversityUniversity of Alberta
Fundersnot available
KeywordsConvertersSeries (stratigraphy)TransformerVoltageComputer scienceCapacitorTopology (electrical circuits)Electronic engineeringElectrical engineeringSeries and parallel circuitsEngineering

Abstract

fetched live from OpenAlex

Transformerless series-connected current source converters (SC-CSCs) were recently proposed. Compared with existing ones, they eliminate the transformer, giving significant reductions in cost and size. However, they need the use of series-connected switches in medium/high-voltage applications, and as a result, very complicated voltage balancing schemes are required. To address this challenge, a modified transformerless SC-CSC is proposed. In the modified one, the series-connected switches are replaced with a cascaded half-bridge converter, while the left remains the same as existing ones. By doing so, the need for series-connected switches is eliminated, while the advantages of original converters are well retained. In addition, the cascaded half-bridge converter has inherent voltage balancing, reduced switching frequencies, and a unique zero-load feature. The operation principle of the modified converter is presented. The performance is verified by both simulations and lab-scaled experiments.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.037
GPT teacher head0.237
Teacher spread0.200 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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