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Real-Time Hardware-in-the-Loop Simulation and Control of Totem Pole PFC Converter

2020· article· en· W3109457558 on OpenAlex
Peyman Amiri, Deepak Gautam, Chris Botting, Wilson Eberle, Liwei Wang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsDelta-Q Technologies (Canada)University of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaDelta
KeywordsTotemConvertersPower factorPower (physics)Computer scienceElectronic engineeringEngineeringOffset (computer science)Electrical engineeringControl systemVoltageControl (management)Topology (electrical circuits)Control theory (sociology)Physics

Abstract

fetched live from OpenAlex

High efficiency totem pole power factor correction (PFC) converters have attracted a significant attention in recent years. State of the art wide band gap (WBG) devices make continuous conduction mode (CCM) totem pole PFC feasible for medium to high power applications. However, higher costs and complex control are the main barriers to widespread industrial adoption of this topology. Control challenges including current spikes during zero crossings, DC component in AC mains current and AC voltage drop handling are investigated in this paper. Appropriate control measures are utilized to address these challenges. Additionally an accurate low cost DC current reduction method is proposed. The effectiveness of the proposed control is verified through real-time hardware-in-the-loop simulation of a 1450 W interleaved totem pole PFC 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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.281
Threshold uncertainty score0.334

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.221
Teacher spread0.210 · 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

Quick stats

Citations7
Published2020
Admission routes2
Has abstractyes

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