Three‐stage SiC‐based bi‐directional on‐board battery charger with titanium level efficiency
Bibliographic record
Abstract
This Letter proposes a novel control and optimisation strategy for a bi‐directional, three‐stage, on‐board battery charger (OBC) achieving 80 PLUS Titanium efficiency. The proposed strategy utilises the benefits of silicon carbide (SiC) devices and is based on direct current hysteretic control (DCHC) with optimisation of switching patterns and dead time. The OBC first stage is a solid‐state transformer that provides the isolation barrier and is operated under zero‐current switching/zero‐voltage switching (ZVS) conditions. The second stage is a bi‐directional buck–boost converter that operates in critical conduction mode (CRM) with automatic dead time optimisation to achieve ZVS operation. The third stage is an H‐bridge inverter with a DCHC controlled current loop to optimise dynamic and steady‐state performance and provide a smooth transition between CRM and continuous conduction mode. The DCHC is implemented using a hybrid software/hardware approach. The experimental results show that the OBC can not only change the power flow direction within a few milliseconds but can also provide reactive power support for the grid. Additionally, the OBC achieves a peak efficiency of 96.65% and a minimum total harmonic distortion equal to 1%.
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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 | 0.000 |
| 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".