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Record W2792433592 · doi:10.1109/tie.2018.2813958

Idle Power Loss Suppression in Magnetic Resonance Coupling Wireless Power Transfer

2018· article· en· W2792433592 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 Industrial Electronics · 2018
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsIdleWireless power transferMaximum power transfer theoremTransmitterElectromagnetic coilPower (physics)Electrical engineeringEngineeringElectronic engineeringPower transmissionCoupling (piping)Maximum power principleInductive couplingComputer scienceChannel (broadcasting)PhysicsVoltage

Abstract

fetched live from OpenAlex

We present a magnetic resonance coupling (MRC) wireless power transfer system that suppresses power losses when operating in an idle state while maintaining high transmission efficiency when operating in an active state. Maximum power can be transferred between transmitting and receiving resonant coils by designing for a simultaneous conjugate match at the source and the load. This match condition, however, leads to high power losses in the transmitting coil when the receiving coil is removed from the system (i.e., when the system is idle). In applications where a device is charged intermittently using a passive charger, the system should be designed by considering power losses in both active and idle states in order to maximize overall system efficiency over time. Here, we show that we can first reduce the idle power losses by introducing mismatch at the transmitter. We can then ensure high active transfer efficiency by introducing a compensating mismatch at the receiver. A four-coil MRC system was built to demonstrate the effectiveness of the idle power loss suppression. By retuning the source and receiver match, the idle power losses were reduced from 38% to 13%, while the active transfer efficiency only dropped from 85% to 76%.

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: Empirical
Teacher disagreement score0.516
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.220
Teacher spread0.205 · 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