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A New Reduced Switch-Count Configuration for Regenerative Cascaded H-Bridge Converter

2020· article· en· W3095186243 on OpenAlexaff
Sarah Badawi, Mehdi Narimani, Zhongyuan Cheng, Navid R. Zargari

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsRockwell Automation (Canada)McMaster University
Fundersnot available
KeywordsConvertersInverterRectifier (neural networks)H bridgePower (physics)Computer scienceRegenerative brakeVoltageEngineeringElectrical engineeringElectronic engineeringAutomotive engineeringPhysics

Abstract

fetched live from OpenAlex

Addition of regenerative capability in high power motor drives have become essential to increase energy efficiency of these systems. To have economic regenerative cascaded H-bridge motor drive, reduction of its switch count has gained the research attention recently in order to have more suitable-sized and more economical drives.This paper proposes a new reduced switch-count power cell configuration for regenerative cascaded H-bridge (CHB) converters. In this cell, four-switch three-phase inverter (FSTPI) is used as the active front-end rectifier instead of the conventional six-switch three-phase inverter. Four-switch three-phase inverter is a common economic solution for the low voltage drives. The proposed cell configuration performance is verified by simulation of a reduced switch-count nine-level CHB. The simulation studies are based on a motor load with both motoring and regeneration operations. The results proves the CHB drive with proposed cell configuration to exhibit promising performance and can offer a cost-effective reduced-switch count regenerative CHB drives.

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 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 score0.986
Threshold uncertainty score0.710

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)0.0010.000

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 head0.041
GPT teacher head0.239
Teacher spread0.198 · 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.

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

Citations4
Published2020
Admission routes1
Has abstractyes

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