Magnetic Field Tuning and Control for Wireless Power Transfer Using Inductive Tuning Plunger and Conical Coils
Bibliographic record
Abstract
Multiple input wireless power transfer (WPT) system has drawn increased interests recently due to its enhancing ability to the efficiency of power transfer. In most cases, it uses a number of transmitters to deliver the wireless power efficiently. These transmitters can be massively used to harvest energy as much as possible and therefore reduces signal and link losses. Powering many devices using massive number of transmitters allows cross coupling occurring. In particular, signals or magnetic fields are mutually induced between transmitters. The goal of this work is to provide an efficient link for wireless power transfer and compensate for the impact of cross coupling. A tuned technique is proposed to optimize the transmit signal for a conical coil transmitter. The proposed scheme efficiently delivers the wireless power by controlling the beam of the magnetic flux. By using this new technique, we then increase the main loop gain of the wireless power signal and reduce the back gain for the receiver in such region. The results are compared to the conical coil. In addition, results illustrate that a tuned transmitter controls the magnetic flux pattern for efficient wireless power transfer.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".