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A Multiport Converter for More Electric Aircraft with Hybrid AC-DC Electric Power System

2021· article· en· W3215265117 on OpenAlexaff
Javad Khodabakhsh, Gerry Moschopoulos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsWestern University
Fundersnot available
KeywordsConvertersFlyback converterTransformerForward converterVoltageElectrical engineeringAC adapterComputer scienceElectronic engineeringElectric power systemĆuk converterBoost converterPower (physics)EngineeringSwitched-mode power supplyPhysics

Abstract

fetched live from OpenAlex

More electric aircraft (MEA) use a heterogeneous combination of AC and DC power generation units and loads. As a result, the electric power system (EPS) of MEA is designed based on a combination of AC and DC voltages at different levels to increase the design's flexibility and improve energy efficiency. However, one of the main drawbacks of such architecture is that many power electronic converters are required to interface different voltage types, which increases system cost, size, and weight. This paper proposes a new multi-port converter to interface an AC distribution system to a high-voltage non-isolated, low-voltage isolated DC system. The isolated system is supplied through the high-frequency isolation transformer designed to operate at a fixed frequency. The proposed converter replaces two conventional AC-DC and DC-DC converters with only six active switches. Furthermore, the converter is operated by a well-known control method without adding complexity to the design procedure. The proposed converter's feasibility is verified with the simulation results obtained from a MATLAB/ Simulink model.

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: Simulation or modeling · Consensus signal: none
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)0.0000.000
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)0.0050.001

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 head0.004
GPT teacher head0.193
Teacher spread0.189 · 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 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

Citations4
Published2021
Admission routes1
Has abstractyes

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