MétaCan
Menu
Back to cohort
Record W3153365064 · doi:10.1109/tpel.2021.3073748

A Generalized Single-Carrier PWM Scheme for Multilevel Converters

2021· article· en· W3153365064 on OpenAlexaff
P. M. Lingom, Joseph Song‐Manguelle, Rodolfo C.C. Flesch, Tao Jin

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2021
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNational Natural Science Foundation of China
KeywordsPulse-width modulationConvertersInverterElectronic engineeringControl theory (sociology)Modulation (music)Computer sciencePower (physics)EngineeringVoltageControl (management)Electrical engineeringPhysics

Abstract

fetched live from OpenAlex

This article proposes a novel and generalized single-carrier (SC) pulsewidth modulation (PWM) scheme suitable for multilevel converters. Compared with the existing SC-PWM schemes, the proposed one presents a simpler approach to replicate the behavior of the phase disposition PWM method at any operating point. Besides having an easier digital implementation, the proposed SC-PWM scheme results in great control flexibility to optimize the operation of multilevel converters. Based on the rationales of the proposed SC-PWM scheme, an optimized switching strategy for a cascaded H-bridge (CHB) multilevel inverter architecture is developed. The proposed optimized switching strategy imposes appropriate switching sequences with a minimum number of power device commutations per cycle, leading to both half-wave and quarter-wave symmetries at the individual H-bridge cell level, which subsequently improves the converter harmonic performances and reduces the overall switching losses. The validity and effectiveness of both proposed modulation and switching strategies are demonstrated through the intensive simulation and experimental test results provided both in time and frequency domains. The experimental results are obtained on a three-phase seven-level CHB inverter for an 18-kW laboratory prototype.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.226
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 teacher head, not a consensus.

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

Citations39
Published2021
Admission routes1
Has abstractyes

Explore more

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