Self-Sustained Oscillating Control Technique for Current-Driven Full-Bridge DC/DC Converter
Bibliographic record
Abstract
This paper presents a novel control approach for a current-driven full-bridge dc/dc converter, which is able to significantly improve the converter performance over a very wide range of operating conditions. The proposed control approach is based on the self-sustained oscillating control (SSOC) scheme, in order to adaptively change the phase shift and the switching frequency of the converter for different operating points. In this control technique, the timing signal is produced based on the transformer primary current, which is a feedback to the control system to determine the switching instants of the power MOSFETs. Therefore, the control system automatically tunes the control variables for different operating conditions. The comprehensive mathematical analysis of the proposed SSOC scheme is presented in detail. The mathematical analysis is based on the geometric viewpoint of the control system, which provides a very good insight into designing the control system. Experimental results provided from a 3 kW prototype confirm the feasibility of the proposed scheme and prove the superiority of the performance compared to the conventional phase-shift control approach.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".