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An SVM Strategy with Two-step Commutation for Isolated AC-DC Matrix Converter

2020· article· en· W3037765018 on OpenAlexaff
Fanxiu Fang, Hao Tian, Yunwei Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCommutationControl theory (sociology)Computer sciencePulse-width modulationVoltagePower (physics)Commutation cellSupport vector machineEngineeringElectrical engineeringArtificial intelligencePhysicsPower factor

Abstract

fetched live from OpenAlex

The isolated AC-DC matrix converter features galvanic isolation and the potential of high-power density. However, to ensure safe operation, the commutation between two bidirectional switches relies on the relative magnitude of input voltages. However, sensor errors and sampling noises can lead to the wrong selection of the commutation sequence, leading to commutation failure. To solve this problem, this paper proposes an SVM strategy to ensure the commutation will happen between two phases with significant differences in magnitude. On the other hand, commutation failure can also be caused when the pulse width is shorter than the required time for the commutation sequence. Hence, the zero vector is optimized to reduce narrow pulses, ensuring the gating signals are long enough to finish the commutation procedures. 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 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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.257
Teacher spread0.244 · 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
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

Citations10
Published2020
Admission routes1
Has abstractyes

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