Time-Domain Analysis and Optimization of a Three-Phase Dual-Active-Bridge Converter With Variable Duty-Cycle Modulation
Bibliographic record
Abstract
The duty-cycle control (DCC) modulation scheme for the three-phase dual-active-bridge (3p-DAB) dc–dc converter is a promising three degree-of-freedom modulation scheme which can extend the converter's soft-switching range and reduce conduction losses under partial loading and wide voltage variations. However, the prior suggested methods to implement DCC in 3p-DABs have drawbacks, such as requiring a multifrequency approximation and offline optimization process, or achieving less than optimal efficiency. To overcome these challenges, this article first proposes an optimal DCC modulation strategy (OMS) for the 3p-DAB based on a novel piecewise time-domain analysis (TDA) and optimization process that obtains the optimal control parameters for minimum rms phase current. Second, this article proposes a novel closed-form minimum current stress optimization (MCSO) DCC scheme based on the theoretical findings of the TDA optimization. The MCSO reduces the transformer phase currents and extends soft-switching operation under partial loading and wide voltage variations. Experimental results show that the proposed closed-form MCSO DCC scheme has virtually identical efficiency as the OMS, making this the first article to provide a closed-form DCC modulation scheme for a 3p-DAB that achieves efficiency results equivalent to a fully optimized offline scheme, but without the drawbacks of the offline optimization process.
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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 | 0.002 |
| 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".