A Manitoba Converter based Bi-directional On-board charger for Plug-in Electric Vehicles
Bibliographic record
Abstract
Conventional plug-in electric vehicle (PEV) battery chargers only allow unidirectional power conversion from grid to the PEV battery hence cannot be used for "Vehicle-to-Grid" functionality in smart grid applications. PEV batteries from different automobile manufacturers come with different charging requirements. Moreover, the grid conditions may vary depending on the charging location. Hence, an universal, dual-stage on-board charger topology is presented that can achieve efficient bidirectional power conversion with a wide input and output voltage range to suit charging requirement of different PEV batteries. The first stage is based on a Manitoba converter, which is a grid-connected converter with bridgeless buck-boost topology that can act as a rectifier or inverter depending on the mode of operation in an extensive range of input-output voltage. The second stage is a high frequency transformer based Dual Active Bridge DC/DC converter to provide galvanic isolation and facilitate bidirectional power flow. The operation of the proposed system is successfully verified in simulation environment as well as its performance experimentally verified by implementation of a 800W hardware prototype.
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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) | 0.007 | 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".