A Half-Bridge Gate Driver With Self-Adjusting and Tunable Dead-Time Modes for Efficient Switched-Mode Power Systems
Bibliographic record
Abstract
The design of high-voltage (HV) switched-mode power systems (SMPSys) poses multiple challenges, such as minimizing the switching losses and preventing possible shoot-through currents, to achieve efficient and reliable operation. This article introduces a reconfigurable half-bridge gate driver (GD) for SMPSys, with an open-drain output configuration, electrostatic discharge self-protection, and two dead-time management modes to address these challenges. The first mode is an externally tunable fixed dead-time generator (FDTG) capable of achieving a wide dead-time range from 5 to 200 ns. The second mode is a self-adjusting dead-time generator (SDTG), designed to adapt to delay mismatches between the GD's channels, regardless of process, voltage, and temperature (PVT) variations, while minimizing dead-time and preventing cross-conduction. The GD was fabricated in an HV 0.18-μm silicon-on-insulator CMOS process technology, supporting a high-side floating bias voltage rail up to 100 V and occupying a core area of 0.285 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . It was tested in a buck converter system using a gallium nitride (GaN)-based half-bridge with a switching frequency of 0.5 to 1 MHz. It achieves a total propagation delay of 11.4 ns and a minimum dead-time of 3.6 ns (3× smaller than state-of-the-art) using its SDTG mode. The system achieved a peak efficiency of 90.5% at an output load of 8 W. Notably, the SDTG mode improves the overall efficiency by up to 20% over the FDTG mode, specifically at higher switching frequencies, showing its effectiveness in enhancing the performance of SMPSys.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".