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Record W2944957401 · doi:10.1109/tpel.2019.2918349

Single-Stage Bidirectional Buck–Boost Inverters Using a Single Inductor and Eliminating the Common-Mode Leakage Current

2019· article· en· W2944957401 on OpenAlexafffund
Ashraf Ali Khan, Yun Lu, Wilson Eberle, Liwei Wang, Usman Ali Khan, Mohammed Agamy, Honnyong Cha

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2019
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInductorCapacitorBuck converterElectronic engineeringVoltageCommon-mode signalBoost converterElectrical engineeringBuck–boost converterLeakage (economics)Computer scienceEngineeringDigital signal processing

Abstract

fetched live from OpenAlex

This paper presents novel single-phase single-stage buck–boost inverters. The proposed inverters provide buck–boost operation for a wide variation of the input dc voltage. In addition, the proposed inverters are bidirectional and provide reactive power. Further, they require only one inductor. The proposed inverters also eliminate the common-mode leakage current by connecting the output neutral to the midpoint of input capacitors or directly to input voltage sources. Therefore, they are well suitable for photovoltaic applications. Although six switches are required, two switches are working at line frequency, resulting in negligible switching loss. Of the four remaining switches, only two are switching at high frequency at a time. The circuit operations are demonstrated through the analysis of the proposed inverters. A 120 Vrms/60 Hz/400 W hardware prototype was constructed and tested. The experimental results verified the theoretical analysis.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
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 head0.023
GPT teacher head0.243
Teacher spread0.220 · 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 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

Citations45
Published2019
Admission routes2
Has abstractyes

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