Optimizing dual half bridge converter for full range soft switching and high efficiency
Bibliographic record
Abstract
This paper is concerned with finding the optimum operating points of a soft-switched dual half bridge bidirectional dc-dc converter. Phase shift modulation (θ) with a fixed duty cycle is used to control the converter [1] but the soft switching range is limited. In this paper the soft switching range and efficiency of the converter are highly improved by recruiting duty cycle (d) as the second control parameter. It is shown that for a wide voltage range on both dc buses, soft switching can be achieved for any power level including zero to full load in both directions. The regions of soft switching on the (θ,d) plane are analyzed and the trajectories of the optimal (θ,d) values for highest efficiencies are extracted. A precise simulated model of the converter is developed to verify and fine tune the analytic results. Finally a 250 KHz, 1.5Kw prototype is designed and implemented to verify the results in practice.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".