Analysis and Design of Bidirectional Parallel-Series DAB-Based Converter
Bibliographic record
Abstract
Unprecedented expansion of renewable, energy storage, and fast charger system applications has diversified the bidirectional converter designs over the past decade. This article presents a new dual-active bridge (DAB) converter topology, which employs parallel and series switches arrangements for low-voltage bridge configurations. The additional switch inclusion provides high dc conversion gain, which enables attractive fast charger applications. The performance of the proposed DAB-based converter with wide dc range has been investigated through several design techniques and comparisons. The use of use of silicon carbide (SiC) devices in higher power conversion significantly improves switching losses. However, unsupervised design will result in significant switching losses and increased electromagnetic emissions. Since the DAB-based converter's high switching frequency allows operation with smaller magnetics, the system stray capacitance plays a critical role. The common-mode current propagated through the system's stray capacitance generates undesired electromagnetic interferences (EMI) and impacts the soft-switching achievable range. To overcome the common-mode current circulation issue, design solutions have been employed to reduce the emergence of system stray capacitance. A harmonic analysis is further discussed along with evaluation of transformer design comparisons. The experimental results show the performance of the DAB-based converter in bidirectional operation and improved common mode current generation with respect to EMI emissions. The simulation and experimental results have been performed using a 5 kW rated power DAB-based converter with SiC power semiconductors.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".