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Record W2126867718 · doi:10.1109/psec.2002.1022579

Development of a bi-directional DC/DC converter for inverter/charger applications with consideration paid to large signal operation and quasi-linear digital control

2003· article· en· W2126867718 on OpenAlexaff
Andrew Swingler, W.G. Dunford

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDuty cycleBattery chargerInverterForward converterNonlinear systemComputer scienceElectronic engineeringDigital controlControl theory (sociology)Power (physics)Ćuk converterController (irrigation)Digital signal processorFlyback converterBoost converterTopology (electrical circuits)Digital signal processingEngineeringElectrical engineeringBattery (electricity)VoltageControl (management)Physics

Abstract

fetched live from OpenAlex

In this paper, a low-power bidirectional DC/DC converter for inverter battery charger applications is considered. Initially, a galvanically isolated and synchronously rectified DC/DC converter topology is prototyped and its stationary performance evaluated. Next, a nonlinear dynamic model of the converter is derived using a state space averaging method. The dynamic model is nonlinear in the sense that it is a function of both converter duty cycle and load. The nonlinear model is then digitized and a proposed simulation algorithm derived and successfully validated against empirical data from the prototype converter. Finally, the large signal circuit dynamics are analyzed and an adaptive, fully digital pole placement controller is examined in adaptive and nonadaptive modes of operation.

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 score0.002
Threshold uncertainty score0.008

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)0.0020.001

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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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

Citations28
Published2003
Admission routes1
Has abstractyes

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