Performance Evaluation of Modulation Techniques in Single-Phase Dual Active Bridge Converters
Bibliographic record
Abstract
This research presents a thorough comparison of different modulation techniques employed in dual active bridge (DAB) converters. The performance of a DAB converter is essentially affected by the modulation technique and the operating point, including power level, input, and output voltages. A deep understanding of different modulations is required to achieve the highest performance in the entire operating range. Therefore, this paper focuses on comparing different modulation techniques over a DAB converter's operating span. The comparison results provide guidance to apply the correct modulation in certain working areas keeping the converter on top of its performance. Moreover, the paper proposes an optimization solution with distinct objective functions adoptable in DAB converters to reduce power loss. The proposed optimization approach outperforms the existing solutions regarding generality and simplicity. The optimization associates with the modulation techniques that include more than one degree of freedom, such as extended phase shift (EPS) and dual-phase shift (DPS). The proposed optimization and the investigated modulation techniques are evaluated in terms of the converter's efficiency, current stress, and backflow power. The evaluation is realized by the simulation study of a 10 kW 800V/500V SiC-based DAB converter in PLECS software.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".