MétaCan
Menu
Back to cohort
Record W1975642616 · doi:10.1109/tpel.2011.2167243

Stability Analysis of Isolated Bidirectional Dual Active Full-Bridge DC–DC Converter With Triple Phase-Shift Control

2011· article· en· W1975642616 on OpenAlexaff
Wu Kuiyuan, Clarence W. de Silva, William G. Dunford

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsConvertersControl theory (sociology)Stability (learning theory)Nonlinear systemPower (physics)Dual (grammatical number)Noise (video)Forward converterComputer scienceBoost converterEngineeringElectronic engineeringTopology (electrical circuits)VoltageControl (management)PhysicsElectrical engineering

Abstract

fetched live from OpenAlex

This paper proposes a new method for stability analysis of a bidirectional dual full-bridge dc-dc converter with triple phase-shift control under arbitrary parameter changes. The present analysis makes the stability determination of these power converters more systematic and precise than the existing methods in this field, which are largely based on simulation. Nonlinear and periodic operation of the bidirectional converter is presented including the control circuit. Using the working theory, the converter operation is separated into several stages. Equivalent circuits and state equations are developed for each stage. The Lyapunov function method is used to determine the stability of the converter in every stage. Justification is provided for the absence of abrupt changes of the state variables or infinite noise at the interface of different stages. The stability of the bidirectional converter is determined theoretically by integrating these concepts. Some simulation results are provided to validate the developments.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.225
Teacher spread0.212 · 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

Citations236
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Power ElectronicsSame topicAdvanced DC-DC ConvertersFrench-language works237,207