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Record W2795622140 · doi:10.1109/tie.2018.2823682

Small-Signal Modeling and Closed-Loop Control of a Parallel–Series/Series Resonant Converter for Wireless Inductive Power Transfer

2018· article· en· W2795622140 on OpenAlex

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

VenueIEEE Transactions on Industrial Electronics · 2018
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsChopperDuty cycleControl theory (sociology)InverterSeries and parallel circuitsMaximum power transfer theoremSmall-signal modelResonant inverterCurrent sourceSeries (stratigraphy)EngineeringPower (physics)Computer scienceElectronic engineeringVoltageElectrical engineeringPhysicsControl (management)

Abstract

fetched live from OpenAlex

Usually, the parallel-compensated inductive power transfer (IPT) topology fed by a current-source inverter is controlled through variable switching frequency and fixed 50% duty cycle method. This enables the system to operate at resonance frequency, which drifts due to load and other parameter variations. Owing to this control constraint, the load requirements are fulfilled by adding extra dc-dc chopper at the output. This paper presents a new control technique for a parallel-series/series IPT network, fed from a full-bridge current-source inverter to meet the load demand directly by an inverter. Therefore, the extra chopper stage at the output side of the converter is eliminated. The control goals are achieved through a two-loop control method, where the inner input current loop controls the source current and the outer output current loop meets the load requirements. The detailed steady-state operation, converter design, small-signal modeling, and control are reported, and experimental results obtained from a 1.6-kW lab prototype are included to verify the mathematical 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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.732
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.029
GPT teacher head0.217
Teacher spread0.188 · 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