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Record W1934216786 · doi:10.1109/ecce.2015.7310605

Soft-switching three-phase matrix based isolated AC-DC converter for DC distribution system

2015· article· en· W1934216786 on OpenAlexaff
Chushan Li, Yulin Zhong, Dewei Xu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRectifier (neural networks)CommutationCapacitorPulse-width modulationInductorTopology (electrical circuits)Forward converterBuck–boost converterSpace vector modulationBuck converterComputer scienceBoost converterFlyback converterĆuk converterThree-phaseElectronic engineeringControl theory (sociology)Power factorEngineeringVoltageElectrical engineering

Abstract

fetched live from OpenAlex

In this paper, a novel three-phase matrix based isolated AC-DC converter is proposed for DC distribution system. The circuit is derived from boost converter based matrix PWM rectifier by only adding a small commutation capacitor and inductor. Compare to traditional power factor correction rectifier plus DC/DC two-stage configuration, the proposed converter has higher efficiency and power density. Soft-switching can be realized for all switches and the intermediate DC capacitor is eliminated in the proposed topology. Also, compared to the buck-derived single stage solution, it requires smaller size EMI filter in the AC input stage. Furthermore, a novel space vector modulation (SVM) scheme is developed for the converter to control the input current and enable the soft-switching operation. In this paper, the topology derivation and circuit operational analysis for soft commutation are given. The proposed SVM scheme is introduced and a simulation is carried out to verify the circuit.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
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 head0.025
GPT teacher head0.257
Teacher spread0.232 · 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

Citations22
Published2015
Admission routes1
Has abstractyes

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