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Record W3120001245 · doi:10.1109/tie.2020.3048284

Commutation Scheme of Seven-Level Hybrid-Clamped Converters With Suppressed Deadband-Induced Voltage Spikes

2021· article· en· W3120001245 on OpenAlexafffund
Hao Tian, Yuzhuo Li, Yunwei Li

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2021
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Alberta
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsConvertersCommutationVoltageControl theory (sociology)CapacitorComputer scienceCommutation cellElectronic engineeringTopology (electrical circuits)EngineeringElectrical engineeringSwitched-mode power supplyControl (management)

Abstract

fetched live from OpenAlex

A seven-level hybrid-clamped (7L-HC) converter is a promising option for medium-voltage drives due to its low number of devices and the ability to well balance all the capacitors. However, like other hybrid-clamped multilevel converters, the freewheeling paths during deadtime can produce unexpected output voltage levels. The unexpected output voltage can cross a few consecutive output levels, introducing a large dv/dt to the system. To address this problem, in this article, we conduct a detailed study of the mechanism that produces such undesirable voltages and propose a commutation scheme to coordinate the turn-on/off sequence of switches in the 7L-HC converters. The proposed method is based on an easy-to-implement bitwise operation of switching vectors, where the number of switching actions is not increased. The proposed method is validated by both simulation and experimental results.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.652
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 integrity0.0000.001
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 head0.040
GPT teacher head0.225
Teacher spread0.185 · 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 designBench or experimental
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

Citations16
Published2021
Admission routes2
Has abstractyes

Explore more

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