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Modeling, Analysis, Design, and Verification of a Reduced Model Capacitive Power Transfer Based Wireless Charging System

2020· article· en· W3097951920 on OpenAlex
Deepa Vincent, 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
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsCapacitanceCapacitive sensingWireless power transferTopology (electrical circuits)WirelessMaximum power transfer theoremPower (physics)Capacitive couplingComputer scienceCoupling (piping)Electrical engineeringDual (grammatical number)Electronic engineeringTransfer (computing)EngineeringPhysicsTelecommunicationsVoltageMechanical engineering

Abstract

fetched live from OpenAlex

In this paper, a reduced capacitance wireless power transfer model is proposed which is suitable for large charging area applications like electric vehicle (EV) charging. Here, when the separation distance between the same side plate pair is large enough, the effect of cross-coupling capacitances diminishes and the analysis based on a reduced capacitance model (RCM) is beneficial. The advantage of using this model is because it attains the unity gain and load-independent operation at designed resonant frequency instead of at dual resonant frequencies in the conventional six capacitance modelling (SCM). A half-bridge dual LC compensated topology is opted for the implementation of the CPT. The system is switched at 1.18 MHz, using GaN switches. The effectiveness of the reduced capacitance modelling is validated experimentally.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.625
Threshold uncertainty score0.946

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)0.0000.000

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 head0.024
GPT teacher head0.200
Teacher spread0.176 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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