Constant Current Fast Charging of Electric Vehicles via a DC Grid Using a Dual-Inverter Drive
Bibliographic record
Abstract
Existing integrated chargers are configured to charge from single- or three-phase ac networks. With the rapid emergence of dc grids, there is growing interest in the development of high-efficiency low-cost integrated chargers interfaced with dc power outlets. This paper introduces a new integrated charger offering electric vehicle fast charging from emerging dc distribution networks. In absence of a dc grid, the charger can alternatively be fed from a simple uncontrolled rectifier. The proposed charger leverages the dual-inverter topology previously developed for high-speed drive applications. By connecting the charger inlet to the differential ends of the traction inverters, charging is enabled for a wide battery voltage range previously unattainable using an integrated charger based on the single traction drive. An 11-kW experimental setup demonstrates rapid charging using constant current control and energy balancing of dual storage media. To minimize the harmonic impact of the charger on the dc distribution network, a combination of complementary and interleaved switching methods is demonstrated.
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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) | 0.002 | 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".