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Record W2571197730 · doi:10.1109/iecon.2016.7793016

An Electrolytic capacitor-less bi-directional EV-Charger with 6 switches

2016· article· en· W2571197730 on OpenAlexaff
Behnam Koushki, Praveen Jain, Alireza Bakhshai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsRippleElectrolytic capacitorCapacitorBattery (electricity)Power (physics)Controller (irrigation)Electrical engineeringBattery chargerReliability (semiconductor)Computer scienceTopology (electrical circuits)Electronic engineeringEngineeringVoltagePhysics

Abstract

fetched live from OpenAlex

In this paper, a new single-stage isolated bi-directional AC-DC converter with the appropriate controller for Electric Vehicle application is proposed. The topology uses only 6 active switches. Single-stage power conversion reduces the cost and volume. Instead of using an Electrolytic capacitor with limited life-time, it uses a film capacitor. This increases the reliability of the system. The low frequency power ripple produced by the single-phase AC-DC power conversion is not allowed to the battery. This increases the life-time of the battery compared to conventional chargers. A three part controller to shape the input current, control the power, and prevent the low frequency power ripple from going to the battery is proposed. Simulation results, as well as experimental results to verify the theory, are presented.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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 designBench or experimental
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

Citations1
Published2016
Admission routes1
Has abstractyes

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