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Record W2944483082 · doi:10.1109/pedes.2018.8707808

Single Carrier-Based Pulse Width Modulator for Modular Multilevel Converters

2018· article· en· W2944483082 on OpenAlexaff
Deepak Ronanki, Sheldon S. Williamson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPulse-width modulationModular designConvertersElectronic engineeringCapacitorComputer scienceModulation (music)WaveformSynchronization (alternating current)VoltageEngineeringTopology (electrical circuits)Electrical engineeringPhysics

Abstract

fetched live from OpenAlex

Carrier-based pulse width modulation (PWM) schemes are the preferred choice for modular multilevel converters (MMCs) due to their simplicity and ease of implementation. However, the required number of carriers for gating signal generation drastically increases with the number of submodules (SMs) in an MMC. These carriers should be accurately synchronized with each other to generate the high-quality output voltage and current waveforms. However, it is difficult to achieve the synchronization due to the memory constraints, sampling issues, computational delays, and control complexity. To overcome these issues, a simple single carrier-based PWM modulator is proposed in this paper. In addition, a simple SM capacitor voltage-balancing approach with less computational burden is presented. The proposed scheme can be easily applied to the n-level MMC without any modifications and applicable to any SM type. The effectiveness of the proposed modulation scheme and SM capacitor voltage balancing algorithm is demonstrated through the simulations in the PLECS®software platform.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.010

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)0.0030.001

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 head0.019
GPT teacher head0.224
Teacher spread0.204 · 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
GenreMethods

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

Citations7
Published2018
Admission routes1
Has abstractyes

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