A ZVS Bidirectional 48-/12-V Converter With Magnetic Integration for 48-V Mild Hybrid Vehicles
Bibliographic record
Abstract
This paper presents a ZVS-bidirectional converter for 48V MHVs. The proposed converter boasts attractive features, including enhanced voltage gain, minimized voltage stresses, a shared electrical ground for input and output, positive output voltage polarity, and continuous low-ripple current on both sides facilitated by the presence of inductors. Additionally, the proposed converter benefits from a single-magnetic core integrating three-winding coupled inductors. In this arrangement, the currents in the second and third windings, which correspond to the currents of the converter’s 12V and 48V sides, are ripple-free, while the first winding experiences a sufficient current swing (i.e., TCM operation) to achieve ZVS. Consequently, both ZVS and current-ripple-cancellation are achieved using this magnetic integration. Mathematical and physical models, as well as magnetic system simulation, are used to elucidate the current-ripple-cancellation and to design the magnetic system. Variable-frequency control is applied to optimize the current ripple according to the output power, improving efficiency. Finally, we present the experimental results of an 800W Si-based prototype that operates under variable-frequency control within a switching frequency range of 250-500 kHz. The converter achieves a peak efficiency of 96.5%, with efficiencies of 96.1% and 96% in boost and buck modes at full-load conditions, respectively. Moreover, the converter retains above 94% power efficiency at above 25% of full load.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".