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Time Domain Modelling of a Wireless Power Transfer System using a Buck-Boost Converter for Voltage Regulation

2021· article· en· W3174294355 on OpenAlexaff
Arpan Laha, Praveen Jain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsWireless power transferBuck converterRectifier (neural networks)Buck–boost converterVoltageDuty cycleTransmitterPower (physics)Boost converterMaximum power transfer theoremComputer scienceWirelessElectronic engineeringControl theory (sociology)Electrical engineeringChannel (broadcasting)EngineeringPhysicsTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a time domain analysis of a Wireless Power Transfer (WPT) system having one transmitter and one receiver in which constant output voltage is maintained by a buck-boost converter placed after the rectifier on the receiver side. The practical modes of operation of the resonant tank are identified, and exact solutions have been derived for the circuit parameters like gain, currents, and voltages in the tank. This helps in preventing overdesign of components from approximate solutions provided by frequency domain modelling. The system is operated in the strongly coupled region below resonant frequency to achieve zero voltage switching (ZVS), by choosing the appropriate duty ratio of the buck-boost converter, which has not been done in existing literature. Experimental results on a 5W, 5V prototype are used to verify the analysis.

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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.644
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
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.196
Teacher spread0.180 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations3
Published2021
Admission routes1
Has abstractyes

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