Ultrafast Transient Response in 48 V Automotive VRMs: An Auxiliary-Assisted Adaptive Slew-Rate Control Scheme
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Bibliographic record
Abstract
This article presents an auxiliary-assisted hybrid dc–dc converter for 48 V automotive voltage regulator modules (VRMs) that enable adaptive inductor-current slew-rate control for ultrafast transient response. The main stage, a 4:1 dual-inductor hybrid (DIH) dc–dc converter, delivers the dc load power, while the output voltage is regulated by a GaN-based auxiliary-buck stage that is ac-coupled by a buffer capacitor. The main stage regulates the output of the ac-coupled auxiliary stage using an average-current-mode-control (ACMC) scheme to achieve adaptive control of the auxiliary-inductor-current slew rate. The auxiliary ac-coupled buck (ACB) converter regulates the output voltage based on an output-capacitor current-based hysteretic-current-mode-control (HCMC) scheme. An adaptive-voltage-positioning (AVP) scheme is proposed for the auxiliary capacitor, which preemptively positions the ACB output voltage for improved transient response. A small-signal model of the auxiliary-assisted converter is presented for stability analysis and validated with simulation results. A 40 W proof-of-concept prototype was fabricated to demonstrate the feasibility of the adaptive slew-rate control technique and AVP scheme. The prototype achieves a peak efficiency of 90.6% with an output capacitance of 500 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{\mathbf{\mu}}$</tex-math></inline-formula>F and an auxiliary capacitance of 22 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{\mathbf{\mu}}$</tex-math></inline-formula>F, while maintaining the output voltage deviation within 50 mV.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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