Design and Magnetic Optimization of Dual Active Bridge Converters for Energy Storage Application
Bibliographic record
Abstract
Dual active bridge (DAB) dc-dc converters are widely used in energy storage systems with low voltage and high current ratings. As the converter may operate at light load operation for extended amount of time, the converter efficiency throughout entire operating range is of great importance. Having an accurate magnetic design and an optimum modulation over entire power range are two of the main factors for any industrial DAB converter. In this paper, a new interleaved transformer winding is proposed for high current applications with parallel turns to achieve equal current sharing. In addition, the dc-bias in transformer caused by asymmetrical enhanced phase-shift (AEPS) modulation is analyzed and a closed-loop control is proposed to mitigate any dc voltage across the low voltage (LV) transformer winding. Using a dc-block capacitor on high voltage (HV) side required for asymmetric modulation and applying the proposed closed-loop control on the LV side, achieving zero dc-flux in transformer is guaranteed. Based on this analysis, a 5kW DAB converter is implemented and full-power efficiency of 98% is achieved at nominal operating point <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\mathrm{V}-\text{LV}=50\mathrm{V}, \mathrm{V}- \text{HV}=400\mathrm{V}$</tex> . The high frequency transformer and current sharing enhancement are verified using finite element analysis and dc-bias elimination is validated in simulation.
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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".