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Record W2809575699 · doi:10.1109/tpel.2018.2846618

A Sinusoidal Pulsewidth Modulation (SPWM) Technique for Capacitor Voltage Balancing of a Nested T-Type Four-Level Inverter

2018· article· en· W2809575699 on OpenAlexaff
Ahoora Bahrami, Mehdi Narimani

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2018
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCapacitorInverterPulse-width modulationVoltageTopology (electrical circuits)Modulation (music)Control theory (sociology)Transient (computer programming)Electronic engineeringComputer scienceElectrical engineeringEngineeringPhysicsControl (management)Acoustics

Abstract

fetched live from OpenAlex

In this letter, a new control method based on the sinusoidal pulsewidth modulation scheme is proposed to control capacitor voltages of a T-type four-level nested neutral-point-clamped (NNPC) inverter. The T-type four-level NNPC inverter has a lower number of switches and components compared with other four-level classic and advanced inverters, which make this topology attractive for high-power medium-voltage applications. This topology has been proposed and studied with the assumption of constant dc sources instead of flying capacitors. In this letter, a simple single-phase modulator is developed to balance flying capacitor voltages. The performance and the feasibility of the proposed control technique are evaluated experimentally under a steady-state and transient conditions and for different modulation indexes and loads. The experimental results demonstrate the effectiveness of the developed control method to control the capacitors' voltages.

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 score0.003

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 communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.231
Teacher spread0.210 · 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

Citations88
Published2018
Admission routes1
Has abstractyes

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