Active power decoupling achieving optimum capacitance requirement with minimal compromise in efficiency
Bibliographic record
Abstract
In single-phase AC/DC converters that achieve unity power factor (UPF) at the AC-side, the power waveform contains a large component at the double-line-frequency (DLF), in addition to the average power. This DLF ripple power can have serious undesirable effects on the load in different applications. In order to prevent it from flowing into the load, the DLF ripple power can be mitigated by connecting a capacitor to the DC-link. However, this method, called passive power decoupling, requires large values of capacitance to be used. For 400(VDC)/kW-level applications, it can be only realized using electrolytic capacitors, resulting in low power-density and low reliability. For applications in which power-density and reliability are more critical, an alternative solution is active power decoupling (APD). In active power decoupling, the storage capacitor has a higher utilization factor because the voltage across it is allowed to have larger variations. This situation can be made possible by separating the capacitor from the DC-link by means of a power electronic converter. The DC/DC buck is the simplest converter that can be used for this purpose. The problem with the buck APD is that it cannot use the theoretically minimum required value of capacitance; although many alternatives have been proposed in the literature, they all bring their own sets of disadvantages. In this work, a superior solution is introduced as an improvement to the buck topology which allows utilization of the theoretically minimum required capacitance with minimal compromise in efficiency. The design details and benefits assessment of this solution are elaborated and its operation is verified using both computer simulation and experiment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".