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Record W2785267815 · doi:10.1109/tpel.2018.2794623

Analysis and Design of Load-Independent ZPA Operation for P/S, PS/S, P/SP, and PS/SP Tank Networks in IPT Applications

2018· article· en· W2785267815 on OpenAlexafffund
Suvendu Samanta, Akshay Kumar Rathore

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2018
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsConcordia University
FundersConcordia University
KeywordsCapacitorMaximum power transfer theoremCompensation (psychology)InverterTopology (electrical circuits)Network topologyControl theory (sociology)EngineeringElectronic engineeringPower (physics)Computer scienceElectrical engineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

The zero-phase-angle (ZPA) operation at inverter output of parallel-compensated inductive power transfer (IPT) topologies is frequently reported to be load dependent. Therefore, either the operating inverter switching frequency or the compensation capacitors are modified dynamically with load variation to reach new ZPA point. This letter proposes a novel design technique of compensation capacitors for several IPT topologies to obtain load-independent ZPA. The proposed method is based on the passive selection of tank network parameters; therefore, it obviates the requirement of dynamic tuning and complexities associated with it. A detailed mathematical analysis is reported, and experimental results obtained from a 1-kW lab-prototype are demonstrated to verify the analysis and performance.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.221
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations50
Published2018
Admission routes2
Has abstractyes

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