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Three-Phase Single-Stage Bidirectional Isolated ACAC Converter with Reduced Count of Switches

2024· article· en· W4396593703 on OpenAlexaff
Asad Hameed, Gerry Moschopoulos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsWestern University
Fundersnot available
KeywordsGalvanic isolationConvertersTransformerForward converterElectronic engineeringPulse-width modulationPower factorBuck converterĆuk converterComputer scienceFlyback converterModulation (music)VoltageControl theory (sociology)EngineeringBoost converterElectrical engineeringPhysicsControl (management)

Abstract

fetched live from OpenAlex

In this paper, a three-phase single-stage bidirectional isolated AC-AC converter with fewer switches than other converters of the same type is proposed. In the proposed single-stage converter architecture, the primary and secondary sides of the two high-frequency transformers are coupled to two four-switch voltage source converters (VSCs), resulting in two dual active half-bridge (DAHB) converters with shared switches. The proposed converter can be controlled using conventional control strategies and can regulate the power flow in both directions by altering the modulation index of sinusoidal pulse width modulation (SPWM) and phase-shift angle. The converter can also perform power factor correction (PFC), in addition to other notable characteristics including galvanic isolation between the primary and secondary sides, step-up and step-down capability and voltage regulation without adding any further converters. This paper presents the operation, control and characteristics of the proposed converter. Experimental results from an experimental prototype that demonstrate the converter's feasibility are presented.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.016
GPT teacher head0.239
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2024
Admission routes1
Has abstractyes

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