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Record W2044650731 · doi:10.1109/tia.2015.2409179

Flyback Mode for Improved Low-Power Efficiency in the Dual-Active-Bridge Converter for Bidirectional PV Microinverters With Integrated Storage

2015· article· en· W2044650731 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Toronto
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaOntario Centres of Excellence
KeywordsFlyback converterFlyback transformerPhotovoltaic systemDual (grammatical number)Electrical engineeringVoltageElectronic engineeringPower (physics)EngineeringBattery (electricity)Topology (electrical circuits)Computer scienceBoost converterPhysicsTransformer

Abstract

fetched live from OpenAlex

This paper targets photovoltaic microinverters (MIVs) with integrated battery storage. The dual-active-bridge (DAB) topology provides bidirectional power flow; however, it generally suffers from poor efficiency and limited regulation accuracy at low power. It is shown that by modifying one switch, the DAB converter can operate as a two-transistor flyback to resolve these two issues. In addition, the dc-link voltage in the two-stage MIV can be dynamically adjusted for optimal performance in DAB mode. The proposed dual-mode control scheme is demonstrated experimentally on a 100-W prototype, with up to 8% increase in converter efficiency at low power.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.021
GPT teacher head0.257
Teacher spread0.236 · 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