A New Integrated Battery Charger (IBC) Architecture for 1200 V Electric Vehicles
Bibliographic record
Abstract
The concept of Integrated Battery Charging (IBC) has garnered considerable interest in the realm of electric vehicles (EVs). This technology leverages existing vehicle hardware for the on-board charging (OBC) function, significantly reducing the total cost and volume of power electronics within an EV. The present work proposes a system-level architecture and model predictive control (MPC) of the IBC based on an active neutral point clamped (ANPC) converter for a 1200-volt EV application. Such high-voltage battery EVs are increasingly favored for their potential benefits, including enhanced charging speed, increased power delivery, and improved efficiency, particularly in high-performance and specialized vehicle segments. Model predictive control is designed for both the battery charging (OBC)/vehicle-to-grid (V2G) and traction modes of operation. Finally, the proposed IBC is modeled in MATLAB/PLECS software for a charging power of 11 kW/bank and 250 kW during the traction mode, and the design is validated.
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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) | 0.005 | 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".