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Record W2889334234 · doi:10.1109/itec.2018.8450186

A Review of Front End AC-DC Topologies in Universal Battery Charger for Electric Transportation

2018· review· en· W2889334234 on OpenAlex
A. V. J. S. Praneeth, Sheldon S. Williamson

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
Typereview
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsConvertersElectrical engineeringNetwork topologyBattery chargerElectric vehicleGridAutomotive industryAutomotive engineeringPower electronicsEngineeringHarmonicPower (physics)Electric-vehicle batteryBattery (electricity)Computer scienceVoltage

Abstract

fetched live from OpenAlex

Electric transportation is the future; the role of power electronics will help achieve better performance. One of the most crucial systems in the electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) is the charging system, in which the front end ac-dc converter connects the grid and the vehicle with high power quality. In North America and Europe, all automotive companies are equipped with level I and level II residential charging for vehicles. Failure to maintain power quality will result in significant impact on customers. Therefore, the charger must achieve high efficiency, power density and low harmonic content. This paper presents a survey of different topologies of power factor correction (PFC) converters in the vehicle on-board charging system.The drawbacks for all the topologies, and their corrective actions in the PFC boost converter, are also briefly discussed.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.045
GPT teacher head0.334
Teacher spread0.290 · 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

Citations65
Published2018
Admission routes1
Has abstractyes

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