Dual Active Bridge Converter with Interleaved and Parallel Operation for Electric Vehicle Charging
Bibliographic record
Abstract
This paper presents the design and optimization of a bidirectional Dual Active Bridge (DAB) converter for electric vehicle battery charging applications, encompassing both heavy and light electric vehicles. The core of this study is a 5.6 kW DAB converter that can seamlessly transition between 3.7 kW and 11.2 kW power outputs to accommodate different vehicle requirements without the need for circuit component changes. This flexibility is achieved through the novel integration of interleaved and parallel operation capabilities, allowing for efficient operation across a broad power range. Key innovations include the design of a high-frequency transformer with dual secondary outputs to facilitate power transfer at high currents up to 30 A, an optimized thermal design, and minimized stress on the circuit board. The use of next-generation power semiconductors and low-loss magnetic circuit elements has resulted in an optimized single-stage bidirectional converter design that showcases enhanced efficiency and competitiveness in the field. Furthermore, the converter’s design enables easy reconfiguration to meet the desired power output, vehicle type, and application needs, making it adaptable for future applications such as Vehicle-to-Grid (V2G) systems. The combination of these features—versatility in power output, efficient high-current transfer, innovative use of power semiconductors, and adaptability for future technologies—positions this DAB converter as a significant advancement in electric vehicle charging technology, offering a scalable solution to meet the evolving demands of electric mobility and renewable energy integration.
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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".