Simplified Hybrid Dual-Bridge LLC Resonant Converter With Reduced Passive Components and Loss for Emergency Power Supply
Bibliographic record
Abstract
The proportion of passive components loss in the total power loss of inductor–inductor–capacitor (LLC) resonant converters has reached a critical point. To address this issue, this article proposes a simplified hybrid dual-bridge LLC resonant converter to reduce passive component losses. It consists of a primary LLC resonant converter and an active clamp auxiliary bridge converter connected in parallel. The turn-off current of the LLC resonant converter over the entire range is greatly reduced by means of the clamping operation of the auxiliary converter. Compared with conventional dual-bridge LLC resonant converters, the proposed converter requires only one resonant tank, which can reduce the number of passive components; therefore, it can achieve a 26.5% resonance component cost reduction and a 13.8% total volume of inductor reduction. A 1.2-kW prototype of the hybrid dual full-bridge (FB) three-leg LLC resonant converters is built as a case study to validate the proposed approach. Compared to conventional dual FB three-leg LLC resonant converters, the proposed converter can achieve a 27% reduction in passive component losses without sacrificing soft switching performance.
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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) | 0.001 | 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) | 0.004 | 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".