Three-phase dual active bridge converter design considerations
Bibliographic record
Abstract
In three-phase dual-active-bridge (DAB) converter, the zero-voltage-switching (ZVS) range, DC capacitor ripple current and converter efficiency are significantly impacted by the selectable system parameters, including transformer turn ratio n, switching frequency f and leakage inductance L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</sub> . The converter performance also varies with different operation conditions, i.e., input voltage, output voltage and output power level. Therefore, these parameters need to be carefully selected to achieve optimized performances. In this paper, a comprehensive study of the parameter selection for the three-phase DAB converter is conducted under different operation conditions. A new parameter fL is defined to reduce the analysis from 3 dimensions to 2 dimensions, which simplifies the analysis of transformer turn ratio significantly. Furthermore, the effective operating area (EOA) of f and L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</sub> are defined for feasible transformer designs. The current stress of switches and DC capacitors are studied in the EOA to help determine the range of f and L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</sub> . Finally, the converter total loss and efficiency are analyzed at full and half load with different input and output voltages. The converter parameter (n, f, L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</sub> ) can be selected using ZVS and efficiency criteria. The tradeoff between high efficiency, wide ZVS area and low capacitor ripple current can be achieved accordingly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".