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Single-Phase Bridgeless Cuk-Derived DC-DC Converter for Vehicle-to-Vehicle Charge Transfer

2021· article· en· W4312626715 on OpenAlexaff
Sukanya Dutta, Akshay Kumar Rathore, Vinod Khadkikar, Hatem Zeineldin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsĆuk converterForward converterBoost converterFlyback converterBuck–boost converterElectric vehicleVoltageElectrical engineeringComputer scienceElectronic engineeringEngineeringPower (physics)PhysicsThermodynamics

Abstract

fetched live from OpenAlex

This work presents the analysis and design of bridgeless Cuk-derived DC-DC converter for vehicle-to-vehicle (V2V) charge transfer as onboard charger. Vehicle-to-Vehicle charging aids in mitigating range anxiety. The converter is designed to operate in discontinuous conduction mode (DCM) thereby reducing the control complexity. The converter has reduced component count making the charger lightweight. Also, the voltage stress of the Cuk-derived DC-DC converter is less compared to conventional Cuk converter. The converter efficiency is high due to low switching losses. This article describes the complete steady state analysis and converter design. Further to validate the analysis, design, and applicability of the converter for vehicle-to-vehicle (V2V) charge transfer, PSIM simulation and laboratory-based hardware prototype results are provided.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

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 integrity0.0000.000
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 head0.035
GPT teacher head0.288
Teacher spread0.253 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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