Thermal management for multi-phase current mode buck converters
Bibliographic record
Abstract
This paper deals with thermal management and power sharing in multi-phase buck converters. In conventional designs, each phase is regulated to share the load current equally. However, due to variations in PCB layout, parasitic resistances, airflow, and transistor on-resistance (Ron), it is common to observe significant temperature variations between the converter phases, leading to reliability issues and suboptimal device utilization. Several past research efforts have demonstrated closed-loop analog and digital techniques to achieve a uniform temperature in all phases. In this work, a thermal management unit (TMU) with four independent linear controllers is proposed to regulate the phase temperatures in a four-phase mixed-signal peak-current mode converter. The digital TMU is designed based on a lumped thermal model of the system and dynamically adjusts the peak current in each phase to match the moving average temperature. Experimental results from a digitally controlled 12 V to 1 V, 50 A, 250 kHz four-phase peak current mode buck converter demonstrate the effectiveness of the proposed thermal management technique in the presence of uneven air flow and dynamic load currents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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 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".