Idle Power Loss Suppression in Magnetic Resonance Coupling Wireless Power Transfer
Bibliographic record
Abstract
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%.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".