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Comparison of magnetic coupling topologies for interleaved multilevel inverters

2021· article· en· W3214206244 on OpenAlexaff
Rita Mattar, Stéphane Lefebvre, Éric Monmasson, Mickaël Petit, Christelle Saber, Marwan Ali

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsSafran Electronics (Canada)
Fundersnot available
KeywordsNetwork topologySizingTopology (electrical circuits)CascadeElectronic engineeringCoupling (piping)Power (physics)Point (geometry)Computer scienceEngineeringElectrical engineeringPhysicsMathematicsMechanical engineering

Abstract

fetched live from OpenAlex

This paper presents a study and comparison in terms of magnetic circuit sizing for two magnetic coupling topologies for interleaved multilevel inverters: the cyclic cascade and the secondary loop. This comparison includes modeling of both topologies and simulation analysis of the sizing of each of them. The interleaved multilevel inverter is then simulated with the sized magnetic components for the system operating point for both topologies. Then, a secondary loop improvement study is developed and simulated to minimize the sizing current for this topology. Finally, an experimental test bench is presented to test and analyze the experimental results for both topologies for a measurement power point of 10 kW.

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)0.001
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.301
Teacher spread0.247 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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