Applying Response Surface Methodology to planar transformer winding design
Bibliographic record
Abstract
Planar transformers provide a light-weight and low profile solution for power electronic converters with highly reproducible parameters. Their parasitic inductances, capacitances, and resistances are difficult to model due to the complex winding arrangement along with their nonlinear and multivariate nature. This paper provides a methodology for determining parametric models for the leakage inductance, inter and intra-winding capacitances, and resistance of planar transformers using a variety of winding arrangements. A Central Composite Design based on the Design of Experiment (DoE) methodology is employed to provide the parametric models using a small number of experimental runs. Results from physical experimentation on a planar ER18/3.2/10 core set are provided and show excellent correlation between modeled results and confirmation testing. The methodology can be employed to characterize and design planar transformers for specific applications (for example soft switching or resonant converters), and to predict their performance as part of different power electronics topologies.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".