Digital Regulation of Wireless Power Transfer Systems Using an Embedded Lock-In Amplifier
Bibliographic record
Abstract
High-performance operation of inductive wireless power transfer (WPT) systems requires judicious tuning of the inverter connected to the transmission hardware for high-performance operation and reliability. In many applications, disturbances to both the coupling condition and the secondary-side load reshape the system dynamics, motivating the design of closed-loop regulation and impedance detection techniques. Although several analog methods have been presented, they require multiple additional components and are dependent upon fixed component values and operating frequency. In this article, a novel digital approach is presented for use in series–series compensated WPT systems. The proposed system extracts both the phase and the magnitude of the primary current in real time. Through closed-loop regulation, zero-voltage switching is sustained without additional compensation components, while the output current is controlled. By utilizing a digital framework, no additional analog components are required, improving system reliability and cost. The state identification method is self-tuning, providing robust suppression of switching noise even with a variable switching frequency. A computationally efficient construction ensures a fast converging measurement and enables high-frequency operation. Analysis, simulations, and experimental results are included to comprehensively verify these characteristics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".