Multiband Adaptive Impedance Compensation Methods for Spatially Robust Capacitive Power Transfer Systems
Bibliographic record
Abstract
This study aims to compare the merits of using both adaptive load resistance and adaptive frequency for impedance compensation in capacitive power transfer (CPT) systems. An adaptive load and frequency-band-switching compensation method is presented that achieves spatial robustness in a CPT system. The method complies with spectrum constraints that limit wireless power transfer to the discrete industrial, scientific, and medical (ISM) frequency bands. Coarse impedance control is obtained by switching frequencies and fine impedance control is obtained by changing load resistance. The method is verified experimentally in a dual-band CPT system operating at two octave-spaced ISM bands: 13.56 MHz and 27.12 MHz. The system is comprised of a six-plate CPT link, class-E inverters, and class-E self-synchronous rectifiers. Adaptive load compensation is implemented at the output of the rectifier. Experimental results show that, with frequency and load compensation, load power can be held constant over a spatial gap that ranges from 4.0 cm to 16.0 cm. Results show that the dual band operation extends the spatial bandwidth of the system by 50% compared to a single frequency system operating at 13.56 MHz.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".