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A Single-Source Three-Phase Six-Level Flying Capacitor-Based Converter

2025· article· en· W4413513698 on OpenAlexaff
Javad Ebrahimi, Suzan Eren, Alireza Bakhshai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsQueen's University
Fundersnot available
KeywordsCapacitorComputer scienceElectrical engineeringVoltageEngineering

Abstract

fetched live from OpenAlex

This paper presents s a six-level flying capacitor-based converter ($6 \mathrm{L}-\text{FCB}$) topology designed for three-phase applications using a single DC source. The proposed topology addresses the limitations of conventional multilevel converters, such as the need for multiple isolated sources, auxiliary balancing circuits, and excessive component count. By employing four flying capacitors per phase and a proper switching-state selection algorithm, the system achieves effective voltage balancing without additional hardware. The topology leverages level-shifted carrier PWM and introduces a priority index-based control strategy that uses phase current direction to regulate capacitor voltages. This enables simplified implementation while maintaining high-quality output voltage with reduced harmonic distortion. A comparison with other sixlevel converters demonstrates the superiority of the proposed design. Simulation results validate the effectiveness of the modulation and balancing techniques under various operating conditions, including changes in load and modulation index.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.036
GPT teacher head0.243
Teacher spread0.207 · 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
Published2025
Admission routes1
Has abstractyes

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