Active Saturation Mitigation in High-Density Dual-Active-Bridge DC–DC Converter for On-Board EV Charger Applications
Bibliographic record
Abstract
This article presents a transformer saturation prevention algorithm (SPA) targeting dual-active-bridge (DAB) dc-dc converters utilized in bidirectional, two-stage electric vehicle (EV) on-board battery chargers. Saturation prevention is achieved by detecting the variation in transformer current slope near the boundary of saturation and applying duty-cycle offsets to the DAB converter full bridges. Compared to alternative methods of saturation mitigation, the proposed algorithm offers the following benefits: Lower transformer design safety margins which enable volume reduction with minimal harm to efficiency, and low-cost implementation using a single low-cost current sensor even at high converter switching speeds. Experiments on a custom 6.6-kW on-board EV charger confirm the controller functionality and initial converter analysis. A peak converter efficiency of 96.8% with a transformer volume of 80 cm3is achieved, which is a 50% volume reduction in comparison to other academic works.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".