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Record W3034939665 · doi:10.1109/tpel.2020.3000497

SVM Strategy for Mitigating Low-Order Harmonics in Isolated AC–DC Matrix Converter

2020· article· en· W3034939665 on OpenAlexafffund
Fanxiu Fang, Hao Tian, Yunwei Li

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2020
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence Fund
KeywordsHarmonicsSpace vector modulationSupport vector machineModulation (music)Electronic engineeringControl theory (sociology)Computer sciencePower (physics)EngineeringPulse-width modulationVoltagePhysicsElectrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Isolated ac-dc matrix converter features bidirectional power conversion, galvanic isolation, and high power density. However, the conventional pulsewidth modulation methods in the literature can lead to the input ac distortions in the isolated ac-dc matrix converter with excessive low-order harmonics. To improve the current quality and maintain a low number of switching actions, an improved space vector modulation (SVM) strategy is proposed in this article. The SVM switching sequence and the distribution of zero vectors are designed to mitigate the low-order harmonics. To verify the performance, an in-depth study of the harmonics generation mechanism in the converter is conducted based on a developed mathematical converter model. The performances of the conventional SVM strategy and the proposed SVM strategy are compared, and simulation and experimental results are provided.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
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 integrity0.0000.001
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 head0.015
GPT teacher head0.239
Teacher spread0.223 · 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

Citations44
Published2020
Admission routes2
Has abstractyes

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