A Drivetrain Integrated DC Fast Charger With Buck and Boost Functionality and Simultaneous Drive/Charge Capability
Bibliographic record
Abstract
Electric vehicles have the potential to change the global driving paradigm, significantly reducing the environmental impact of transportation systems. However, charging infrastructure cost and range anxiety impose challenges on rapid technology adoption. This paper proposes an onboard integrated dc charger, leveraging the traction inverter, and motor winding inductance to ensure the minimum incremental mass. The proposed circuit allows the vehicle to connect directly to emerging dc microgrids, utility storage, or renewable energy resources. The system is compatible with power supply voltages higher or lower than the vehicle battery, offering the possibility to charge 400-V batteries from emerging 1000-V supplies, as well as 800-V battery from the existing 600-V dc interfaces. The presented method also provides bidirectional fault blocking capability and bidirectional power transfer, suitable for V2G, G2V, or V2V operation. In addition, this paper proposes simultaneous driving and charging, especially useful for semitrailer trucks applications, significantly increasing operational range. The solution presented in this paper offers a simple and safe charging scheme with the potential to substantially reduce charging infrastructure cost and address range anxiety.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".