Design Optimization Methodology for Planar Transformers for More Electric Aircraft
Why this work is in the frame
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Bibliographic record
Abstract
Isolated DC-DC converters are considered the building blocks of modern aircraft electrical power networks. The high-frequency transformer utilized in such converters is the major contributor to the size and weight besides the thermal management system. In this paper, an optimization design methodology aims to minimize the transformer core size and improve the converter performance through optimized winding configurations. The transformer core selection is based on optimizing the maximum flux density while considering different magnetic materials and number of cores in parallel. The trade-offs between the converter efficiency and core weight in selecting an optimum switching frequency are presented. Multi-layer minimum gradient (MLMG) winding configurations are proposed to eliminate the high-frequency oscillations (HFO) caused by the transformer parasitics. The proposed configurations resulted in a reduction of the intra-winding capacitance by 15 times with 20 <formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex>$\%$</tex></formula> improvement in the transformer volume as compared to a similar conventional double-layers spiral configurations. Numerical simulations are performed in ANSYS Maxwell to validate the proposed design. The effect of the different configurations on the converter performance is verified in the PLECS simulation environment. PLECS simulation results are validated experimentally for the conventional and proposed configurations highlighting the improvements on the performance of the converter.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it