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Record W2146303274 · doi:10.1109/isie.2009.5214290

A new high power efficiency cascaded U cells multilevel converter

2009· article· en· W2146303274 on OpenAlexaff
Youssef Ounejjar, Kamal Al-Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsRectifier (neural networks)VoltageCapacitorTopology (electrical circuits)Power (physics)Boost converterElectronic engineeringInverterComputer scienceForward converterEngineeringControl theory (sociology)Electrical engineeringControl (management)Physics

Abstract

fetched live from OpenAlex

In this paper, authors presents a novel competitive multilevel converter. The novel cascaded U cells topology is constituted from two power switches and one capacitor for each cell. In case of DC/AC conversion, the proposed fifteen level inverter allows a nearly sinusoidal output voltage resulting on a perfectly sinusoidal load current. In case of AC/DC conversion, the proposed fifteen level rectifier presents a reduced impact on the utility supply, a good energetic efficiency and a small number of power switches and passive components. An average model of the proposed converter is performed and a control strategy is designed in order to draw a nearly sinusoidal current and voltage. Active and passive filters can thus be avoided resulting on a highest energetic efficiency and a reduced installation cost. The proposed converter presents also the possibility and the simplicity of changing the number of voltage levels only by acting online on the ratios of the desired output voltages. The modeling and control strategy of the proposed fifteen level converter were verified by simulation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.934
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)0.0030.001

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 head0.007
GPT teacher head0.191
Teacher spread0.184 · 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; both teacher heads agree on what is shown here.

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

Citations30
Published2009
Admission routes1
Has abstractyes

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