A Dual-Active Bridge Converter With a Wide Output Voltage Range (200–1000 V) for Ultrafast DC-Connected EV Charging Stations
Bibliographic record
Abstract
This article proposes a wide voltage range bidirectional dc/dc charging converter. The proposed converter interfaces the fixed charging station dc-bus to the electric vehicle (EV), featuring a 200–1000-V charging voltage range. The wide voltage range is critical for future proofing of charging stations to support the existing and next-generation EVs, while also enabling its use for different applications, leading to major benefits in the economy to scale. Multiple charging converters have been previously proposed, but rarely has there been one which focused on the special needs of a dc-connected station while also considering a universal charging voltage range and cost-effectiveness. As such, a universal charging converter is proposed to fill the research gap and address the said needs. First, the proposed topology is introduced, and the operation principle and mode-transitioning scheme are analyzed. A converter design optimization strategy is also proposed, specifically for EV chargers, which takes an energy-based approach using data collected from actual EVs’ charging sessions. The experimental results and analysis for the 10-kW, 1-kV converter prototype validate the feasibility of the proposed converter, performance, and design approach.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".