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Real-Time Simulation of a Neutral Point Clamped Dual Active Bridge Converter

2022· article· en· W4377972203 on OpenAlexaff
Karim Meddah, Téo Robert, Emmanuel Rutovic, Romain Monthéard, Tarek Ould‐Bachir

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsPolytechnique Montréal
FundersCalifornia Earthquake Authority
KeywordsConvertersField-programmable gate arraySolverLatency (audio)Computer scienceHalf bridgeBridge (graph theory)Dual (grammatical number)Electronic engineeringReal-time simulationDiodeEngineeringSimulationElectrical engineeringComputer hardwareCapacitorVoltage

Abstract

fetched live from OpenAlex

This paper presents a new approach for the modeling and real-time simulation of power electronic converters (PECs) switched at high frequencies. The proposed method is based on the modified-augmented nodal analysis to determine the matrix equations. It uses the previous time-point current of each diode and checks against its previous state to determine the next state. This research shows how precise real-time modeling of the HSF of PEC may be achieved using low-cost FPGA systems. The suggested platform employs a solver to ascertain the status of uncontrolled switches. The performance of the presented method is evaluated using a test scenario using a Dual Active Half-Bridge circuit. The research shows that the suggested solution achieves a time-step of 32 ns while being latency and resource-efficient.

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.228
Teacher spread0.217 · 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
Published2022
Admission routes1
Has abstractyes

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