Design of Variable Inductor for Powertrain DC-DC Converter
Bibliographic record
Abstract
Variable Inductor (VI) uses a small control current to modulate the permeability of a magnetic core and regulate its characteristics. This makes it suitable for applications with a stringent space limitation and a wide range of load variations. Nonetheless, this device is composed of multiple windings and several quantities can be used. Hence, its design is a demanding task and it is even much more complex in case of electric vehicles (EV) converters. This paper provides a systematic design procedure of VI taking into consideration of the nature and requirements of a three-wheel recreational electric vehicle. A VI is designed for a 33 kW nominal and 82 kW peak bidirectional DC-DC converter. Unlike the classical methods, the design procedure is based on the RMS current rather than the peak current. The designed VI is evaluated with FEM simulations. In comparison to the peak current design, the RMS based design and the use of VI resulted in 46% volume reduction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 0.000 |
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 teacher head, 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".