An <i>LCC</i> Wireless Charger With Embedded Cell Equalization via a Shared Compensation Inductor
Bibliographic record
Abstract
This paper presents an integrated approach for achieving simultaneous battery charging and balancing in wireless power transfer (WPT) systems, unifying both functions within a single, compact circuit topology. The proposed design repurposes the receiver-side compensation inductor as the primary winding of a multi-winding transformer, enabling the balancing function to be realized without introducing additional magnetic components or control circuits. Balancing voltages and accurate inter-cell energy redistribution are governed by the transformer's turns ratio, allowing precise regulation without auxiliary converters or switch matrices. Consequently, the system avoids the multiple receiver coils and complex switching networks typical of conventional WPT equalizers, leading to notable reductions in cost, volume, and control complexity. Furthermore, the topology ensures accurate balancing without stringent coupling consistency and remains stable under coil misalignment, highlighting its robustness to mutual inductance variations. These attributes make the system particularly suitable for dynamic or mobile energy storage applications. Experimental results validate the proposed equalizer, demonstrating a charging efficiency of 81.5% at a 19 W load while maintaining inter-cell voltage deviations below 0.02 V. These results demonstrate that the proposed method offers a compact, reliable, and scalable approach for integrated battery management in WPT-enabled systems.
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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) | 0.000 | 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".