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Record W2535420019 · doi:10.1109/poweri.2014.7117622

Small-signal analysis of boost converter, including parasitics, operating in CCM

2014· article· en· W2535420019 on OpenAlex
Haytham Abdelgawad, Vijay K. Sood

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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsParasitic extractionTransfer functionConvertersControl theory (sociology)Boost converterController (irrigation)Small-signal modelTransient (computer programming)State spaceTransient responseComputer scienceElectronic engineeringBuck–boost converterThermal conductionVoltageEngineeringMathematicsPhysicsElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

This paper presents the various principles of statespace averaged modeling of DC-DC Boost converters operating in the continuous conduction mode (CCM). The average model technique, the time average algorithm, and the energy conservation laws are used. Also, the output transfer function of a Boost converter is derived which can be used for designing a robust controller. Furthermore, the effects of parasitic elements and losses are included based on the state-space averaging technique. The open loop transfer functions of the proposed models are derived and the behavior of the converter is verified by the transient step responses.

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: none
Teacher disagreement score0.699
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.243
Teacher spread0.220 · 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

Citations28
Published2014
Admission routes1
Has abstractyes

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