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Frequency Domain Analysis of a Wireless Power Transfer System Operating in a Wide Load and Coupling Range Using Frequency Modulation of Inverter for Voltage Regulation

2022· article· en· W4280625939 on OpenAlexaff
Arpan Laha, Abirami Kalathy, Praveen Jain

Bibliographic record

Venue2022 IEEE Applied Power Electronics Conference and Exposition (APEC) · 2022
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsWireless power transferHarmonicsInverterCapacitorMaximum power transfer theoremTransmitterVoltageHarmonic analysisCoupling (piping)Electronic engineeringElectrical engineeringPower (physics)EngineeringElectromagnetic coilPhysicsChannel (broadcasting)

Abstract

fetched live from OpenAlex

An accurate frequency domain analysis in the steady state has been introduced for a Wireless Power Transfer (WPT) system which maintains output voltage regulation by frequency modulation of inverter switches. The modelling has been shown for both continuous (CCM) and discontinuous (DCM) modes of operation considering harmonics on both sides of the resonant tank. This accurate analysis can be used for proper design and selection of system components such as the resonant capacitors, WPT coils and semiconductor devices. Two different characteristics of the system are identified based on the coupling coefficient between the transmitter and receiver coils and output load resistance range. Characteristic I, in which the inverter switches can be operated below the resonant frequency of the system to achieve zero-voltage switching (ZVS), is demonstrated in this paper for the first time. Experimental results on a 5W WPT system demonstrate the two different characteristics of the system and validate the accuracy of the analysis presented in this paper.

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)0.001
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: Empirical
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.203
Teacher spread0.194 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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