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Record W4226277395 · doi:10.1109/tpel.2022.3147258

Generalized Low Switching Frequency Modulation for Neutral-Point-Clamped and Flying-Capacitor Four-Level Converters

2022· article· en· W4226277395 on OpenAlexafffund
Mingzhe Wu, Hao Tian, Kui Wang, Georgios Konstantinou, Yunwei Li

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2022
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConvertersCapacitorPulse-width modulationModulation (music)Control theory (sociology)Modulation indexHarmonicVoltagePower (physics)Operating pointElectronic engineeringComputer scienceTopology (electrical circuits)PhysicsEngineeringElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

Four-level neutral-point-clamped (NPC) and flying capacitor (FC) converters are suitable candidates for high-power medium-voltage applications due to their desired output performance and high power density. The major challenge on their successful applications lies in the dc-link capacitor and FC imbalance issue, especially for converters without redundant states that result in a significantly reduced control flexibility. In this article, a generalized low switching frequency modulation scheme based on selective harmonic elimination pulsewidth modulation (SHE-PWM) is proposed that can be applied to all types of 4L-NPC and 4L-FC converters. To address the dc-link capacitor and FC imbalance problems, the capacitor charge objective is formulated and incorporated into the nonlinear equations of SHE-PWM in solving the switching angles, which would then possess natural capacitor balancing ability. Four effective solutions are provided to address the reduced solution space issue with this formulation in high modulation index range for natural capacitor balancing, thus the full range operation can be guaranteed. Simulation and experimental results are presented to verify the effectiveness of this generalized modulation for 4L-NPC and 4L-FC converters.

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)
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 score0.815
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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.215
Teacher spread0.195 · 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

Citations13
Published2022
Admission routes2
Has abstractyes

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