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Record W3126599485 · doi:10.1109/tia.2021.3056493

A New Space Vector Modulation Strategy to Enhance AC Current Quality of Isolated DC–AC Matrix Converter

2021· article· en· W3126599485 on OpenAlexafffund
Fanxiu Fang, Hao Tian, Yunwei Li

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2021
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence Fund
KeywordsSpace vector modulationCommutationHarmonicsDuty cycleWaveformComputer scienceGalvanic isolationModulation (music)Electronic engineeringForward converterPulse-width modulationControl theory (sociology)CapacitorVoltageEngineeringBoost converterElectrical engineeringPhysicsTransformer

Abstract

fetched live from OpenAlex

The isolated dc-ac matrix converter is a promising option to connect dc system and ac system, performing directional power conversion and providing galvanic isolation. Due to the absence of the bulky dc-link capacitor, the converter can be compact. However, when a conventional modulation method is applied to the converter, the coupling of H-bridge and matrix converter will result in numerous harmonics in ac current. This article proposes a new space vector modulation (SVM) strategy for isolated ac-dc matrix converter. It improves the duty cycle calculation to reduce the harmonics in ac current while the number of switching actions remains low. Furthermore, considering the essential commutation process of matrix converter can also impact waveform quality, two-step commutation and optimized zero vectors are adopted to reduce narrow pulsewidth modulation pulses, ensuring the gating signals are always long enough to finish commutation. Simulation and experimental results are provided to verify the performance of the proposed SVM strategy.

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 score0.971
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.321
Teacher spread0.290 · 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

Citations20
Published2021
Admission routes2
Has abstractyes

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