Sequential Mutual-Inductance Identification Method for Wireless Power Transfer Systems of Electric Vehicles
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Bibliographic record
Abstract
In a multi-transmitter static wireless power transfer (WPT) system for electric vehicles (EV), the transmitter-to-receiver mutual-inductance value is required to assign current to each transmitter. This article proposes a sequential mutual-inductance identification method (SMIM) that identifies the transmitter-receiver mutual inductance transmitter by transmitter in sequence. The proposed method simplifies the multi-transmitter system into a single-transmitter system through the current blocking principle. The identification only requires measuring the magnitude of DC bus voltage and transmitter rms currents where no receiver-side sensor is needed. The mutual-inductance can be obtained through simple calculations with low computation requirements. It is demonstrated that SMIM robustness against transmitter self-inductance deviation is greatly enhanced by introducing a two-point identification technique. High SMIM accuracy is achieved by optimizing test conditions over the entire viable charging zone of WPT system. The experimental results demonstrate a maximum 3.11% error in identified mutual-inductance, provided coupling coefficient exceeds 0.02.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it