MétaCan
Menu
Back to cohort
Record W4387362873 · doi:10.1109/tie.2023.3317836

Reduction of Common-Mode Voltage and NP Voltage Oscillation for Three-Level Vienna Rectifiers Using Alternative Phase Opposition Disposition PWM

2023· article· en· W4387362873 on OpenAlexaff
Peng Zhang, Xuezhi Wu, Bowei Li, Li Ding, Long Jing, Weige Zhang, Yunwei Li

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2023
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCommon-mode signalPulse-width modulationControl theory (sociology)VoltageOscillation (cell signaling)PhysicsMathematicsElectronic engineeringComputer scienceEngineeringElectrical engineeringChemistryArtificial intelligence

Abstract

fetched live from OpenAlex

In this article, a simple pulse width modulation (PWM) method based on zero-sequence component injection and alternative phase opposition disposition PWM (APODPWM) is proposed for three-level Vienna rectifiers to simultaneously reduce the common-mode voltage (CMV) and mitigate the neutral-point (NP) voltage oscillation. First, to avoid using the small vectors with high CMV, the range limitation of the zero-sequence component is investigated. Then, a specific zero-sequence component that satisfies the above limitation is calculated and injected into three-phase reference signals to balance the NP voltage. Moreover, for the zero-crossing intervals where the NP voltage oscillation cannot be suppressed, a coordinating factor is introduced to adjust the maximum and minimum reference signals for reducing the spike NP current. Finally, the effectiveness and performance of the proposed method are verified by experimental results.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.082
GPT teacher head0.306
Teacher spread0.223 · 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 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

Citations8
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Industrial ElectronicsSame topicMultilevel Inverters and ConvertersFrench-language works237,207