Low-Profile Fractional Planar Transformer Based on a Novel Infinite-shape pcb winding For 5kW Dual Active Bridge Converter
Bibliographic record
Abstract
The pursuit of high power density and high-frequency converters has driven advancements in passive components. Planar transformers have emerged as crucial elements in high power density designs due to their low profile and ease of manufacturing. However, in higher voltage applications, ferrite cores with substantial effective core area and higher number of turns are necessary to prevent core saturation. In this paper, a new infinite-shape winding is proposed which employs the side legs of E cores to obtain double effective turns. A planar transformer is proposed using the infinite-shape winding and a ELP 64/10/50 core for a 48V-400V Dual Acitve Bridge (DAB) converter opertaing at 120kHz. By employing a single infinite-shape winding on the 48V side, equivalent to two effective turns, the high-voltage side pcbs can fit into a lower-profile core while maintaining minimal inter-winding capacitance. To meet the demands of this high-power application, parallel infinite-shape pcbs are utilized to increase current capability. A novel interleaving method is proposed to achieve balanced magnetic field exposure and equal current distribution for the parallel windings effectively reducing ac resistance. Finite Element Analysis (FEA) simulations verify the performance of the proposed transformer, demonstrating perfect current distribution and copper utilization. A 5kW DAB converter utilizing the proposed planar transformer is built that achieves 98% efficiency at full power and 3.7 kW/L power density, while the transformer itself reaches 43 kW/L power density with 99.75% efficiency at full load operation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".