A Canonical Filter Theory Approach for the Synthesis of Inductive Wireless Power Systems with Multiple Resonators
Bibliographic record
Abstract
The advantage of the canonical filter theory approach to design inductive power transfer (IPT) systems is that values for the coupled resonator elements are readily calculated from scaled canonical filter prototypes with specific frequency response characteristics.For example, Butterworth bandpass filter prototypes can be used to synthesize resonant-coupled IPT systems with criticallycoupled frequency response characteristics.In this work, we analyze two canonical filter prototype structures: one prototype has series matching elements at the ports, and the other prototype has shunt matching elements at the ports.Equations are provided to transform the networks into coupled resonator structures that implement IPT links with a transmitter, receiver, and multiple repeater coils.The filter methodology for IPT link synthesis also provides an easy framework to evaluate design trade-offs.An example of comparing resonator inductor sizes for both the series and shunt matching topologies is shown for IPT links operating in ISM frequency bands of 6.78 MHz, 13.56 MHz, 27.12 MHz, and 40.68 MHz.Experimental results are shown for four different IPT examples that were designed using filter synthesis methods.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".