Self-Tuning Digital Current Estimator for Low-Power Switching Converters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An inductor current estimator suitable for low-power digitally controlled switch-mode power supplies (SMPS) is introduced. The estimation of the average current value over one switching cycle is based on the analog-to-digital conversion of the inductor voltage and consequent adaptive signal filtering. The adaptive filter is used to compensate for variations of the inductance and series equivalent resistance affecting accuracy of the estimation. Based on the response to an intentionally introduced and known current step, the filter tunes its own parameters such that a fast and accurate estimation is obtained. A practical realization of the estimator resulting in a modest increase in digital controller complexity is shown. Besides a simple digital IIR filter and a load step circuit, it only requires a slow analog-to-digital converter for the input voltage measurement. The estimator is tested on a 6.5 V to 1.5 V, 15 W, digitally-controlled buck converter prototype. The results show that between 20 % and 100 % of the maximum output load the estimator has accuracy better than 10 % and one switching cycle response time.
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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 | 0.000 | 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 | 0.001 |
| 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 it