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Record W2204679727 · doi:10.1109/vppc.2015.7353019

Single-Phase Single-Switch Vienna Rectifier as Electric Vehicle PFC Battery Charger

2015· article· en· W2204679727 on OpenAlex

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 institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsRectifier (neural networks)Battery chargerPower factorRippleElectrical engineeringPrecision rectifierVoltageTopology (electrical circuits)Battery (electricity)Controller (irrigation)HarmonicAC powerThree-phaseWaveformPower (physics)EngineeringComputer sciencePhysics

Abstract

fetched live from OpenAlex

This paper presents a single-phase single-switch bridgeless power factor corrector (PFC) boost Vienna rectifier as an onboard electric vehicle (EV) battery charger. The presented topology generates 3-level voltage waveform at the input which eliminates harmonic contents significantly while using small filters. The reduced number of parts used in this topology makes it appealing for EV industries to develop this PFC rectifier as a compact battery charger. Modelling of the single- phase Vienna rectifier is performed and a cascaded PI controller is designed to regulate the DC bus voltage at 400V to charge EV batteries as well as drawing low harmonic grid current and ensuring unity power factor operation of the converter. Simulations are done to validate the good dynamic performance of the single-switch rectifier and adopted controller in generating regulated and low ripple DC voltage from AC grid to supply EV batteries.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.401
Threshold uncertainty score1.000

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)0.0010.002

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 head0.033
GPT teacher head0.247
Teacher spread0.214 · 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

Citations49
Published2015
Admission routes1
Has abstractyes

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