MétaCan
Menu
Back to cohort
Record W2751517699 · doi:10.1109/tpel.2017.2750081

A New Inductive Power Transfer Topology Using Direct AC–AC Converter With Active Source Current Waveshaping

2017· article· en· W2751517699 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2017
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsConcordia University
FundersConcordia University
KeywordsMaximum power transfer theoremTopology (electrical circuits)Buck–boost converterComputer scienceElectronic engineeringBuck converterVoltage sourceAC powerPower (physics)Current sourceBoost converterElectrical engineeringEngineeringVoltagePhysics

Abstract

fetched live from OpenAlex

Generally, in wireless inductive power transfer (IPT) system, the power is processed through multiple power transfer stages and this leads to lower efficiency and higher cost of the system. Recent research shows that the use of a direct ac–ac converter in an IPT system compensates these limitations significantly. However, one of the major challenges of the IPT circuit with direct ac–ac converter is to achieve multiple control goals through a single converter. These include load power requirement, maintaining high-quality source current and achieving soft switching of inverter switches, etc. In the existing literatures, the research is more focused on meeting load power requirement and soft switching of inverter switches. The major focus of this paper is to propose, analyze, and control a new IPT power converter topology using current-fed direct ac–ac converter. Compare with existing buck derived, i.e., voltage source ac–ac converter topologies, the proposed topology is boost derived; therefore, active source current waveshaping is easily obtained. The complete control is carried out through two loops, where the outer output current loop ensures load requirements and inner loop maintains the high-quality grid current. The detail of steady-state and dynamic analysis and design procedure of the converter is presented. Experimental results obtained from a 1.2-kW lab-build prototype are included to verify the analysis and proposed control.

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 score0.835
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.244
Teacher spread0.228 · 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