Sensorless Digital Peak Current Controller for Low-Power DC-DC SMPS Based on a Bi-Directional Delay Line
Bibliographic record
Abstract
Peak current mode control is challenging to implement in integrated dc-dc converters for sub 1 W applications due to the need for an integrated high-bandwidth, low-noise current sensor. The analog sensor must typically consumes less than a few hundred micro-amps while amplifying the current through the high-side switch, which has frequency components extending into the ten's of MHz. Sensorless current mode control (SCM) eliminates the need for an explicit current sensor by reconstructing the inductor current from the system input/output voltages and the PWM signal pulse-width. In this work, a bidirectional delay line based digital SCM scheme is proposed. The inductor current is mapped onto the bi-directional delay line whose propagation delay tracks the inductor current slopes. An integrated digital current observer designed in a 0.18μm CMOS process is compared to a benchmark analog current sensor operating at 2 MHz and fabricated in the same process. The digital current observer consumes 168μA, or 20% less then the benchmark at Iout= 100 mA, while avoiding signal-to-noise degradation at light loads. A prototype of the digital current sensor operating at 1 MHz is demonstrated on a CPLD platform.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".