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Three-Phase Single-Stage Multiport AC-DC Converter with Integrated DC-DC Conversion Stages

2025· article· en· W4409991668 on OpenAlexaff
Asad Hameed, Gerry Moschopoulos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsWestern University
Fundersnot available
KeywordsCharge pumpDC biasFlyback converterForward converterElectrical engineeringDC motorComputer scienceElectronic engineeringVoltageCapacitorEngineeringBoost converter

Abstract

fetched live from OpenAlex

A new three-phase multiport AC-DC converter with integrated DC-DC conversion stages is introduced in this paper. The converter features one three-phase AC port and three DC ports: one AC port and one DC port are bidirectional, while the remaining two DC ports are unidirectional. The proposed converter is formed by combining three sub-converters: a buck DC-DC converter, a three-phase full-bridge DC-DC converter, and a three-phase six-switch AC-DC voltage source converter (VSC). All sub-converters share the same switches to operate as a single-stage converter. The converter ensures a unity power factor at the AC port and offers galvanic isolation at one of the DC ports. All ports can be independently controlled, except for one DC port. The proposed converter topology is straightforward, using only six active switches and requiring a standard control system for operation. Additionally, when used in a microgrid, this converter can eliminate the need for two other converters, significantly reducing both the size and complexity of the system. This paper defines the workings, characteristics, and control of the proposed converter. Additionally, scaled-down prototype experimental results are provided to validate the converter.

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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.018
GPT teacher head0.236
Teacher spread0.218 · 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
Published2025
Admission routes1
Has abstractyes

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