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Record W2754549379 · doi:10.1109/tpel.2017.2751419

A New Boost Switched-Capacitor Multilevel Converter With Reduced Circuit Devices

2017· article· en· W2754549379 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2017
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSwitched capacitorCapacitorVoltageBoosting (machine learning)Topology (electrical circuits)Network topologyElectronic engineeringPower electronicsComputer scienceElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

In this paper, a novel platform for the single phase switched-capacitor multilevel inverters (SCMLIs) is presented. It has several advantages over the classical topologies, such as an appropriate boosting property, higher efficiency, lower number of required dc voltage sources, and other accompanying components with less complexity and lower cost. The basic structure of the proposed converter is capable of making nine-level of the output voltage under different kinds of loading conditions. Hereby, by using the same two capacitors paralleled to a single dc source, a switched-capacitor (SC) cell is made that contributes to boosting the value of the input voltage. In this case, the balanced voltage of the capacitors can be precisely provided on the basis of the series-parallel technique and the redundant switching states. Afterward, to reach the higher number of output voltage levels, two suggested SC cells are connected to each other with a new extended configuration. Therefore, by the use of a reasonable number of required power electronic devices, and also by utilizing only two isolated dc voltage sources, which their magnitudes can be designed based on either symmetric or asymmetric types, a 17- and 49-level of the output voltage are obtained. Based on the proposed extended configuration, a new generalized version of SCMLIs is also derived. To confirm the precise performance of the proposed topologies, apart from the theoretical analysis and a complete comparison, several simulation and experimental results are also given.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
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 science0.0010.000
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 head0.017
GPT teacher head0.223
Teacher spread0.206 · 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