A Compact Vertically Stacked Converter Module with Thermal Balancing and High-Power Dissipation Capability
Bibliographic record
Abstract
A compact vertically stacked buck converter is designed with improved thermal performance. Three copper core PCBs and two vertical double-diffused MOSFETs (VDMOS), in TO-Leaded Topside-Cooled (TOLT) package, are stacked together to form the half-bridge output stage. The inductor, the input and output capacitors, and the gate driver ICs are also assembled in this module. For comparison purposes, a horizontally laid out buck converter with the same components using a conventional FR4 PCB is also built. Under forced air cooling, the proposed vertically stacked 48 to 12 V buck converter, switching at 355 kHz, can achieve an output power of more than 160 W with a peak temperature of 81 degree Celsius. The same buck converter in horizontal configuration can only achieve a maximum output power of 60 W with a peak temperature of 90 degree Celsius. At 60 W output, the hottest point for the proposed vertically stacked converter is 23 degree Celsius lower than that of the conventional PCB layout. Moreover, the power conversion efficiency of the proposed vertically stacked converter is improved at the same 60 W power level. Switching at 244 kHz with optimized deadtimes, the maximum output power of the vertically stacked converter is measured to be 291 W. Benefited from the high-power dissipation capability, the converter can maintain a nearly constant efficiency across a wide range of output power from 194 to 291 W.
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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 | 0.000 |
| 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".