Smart IGBT's for Advanced Distributed Ignition Systems
Bibliographic record
Abstract
<div class="htmlview paragraph">Driven by factors like consumption, power output per liter, comfort and more stringent exhaust gas standards the powertain control area, has developed rapidly in the last decades. This trend has also brought with it many innovations in the ignition application. Today we can see a trend to Pencil-coil or Plug-top-coil ignition systems. The next step in system partitioning is to remove the power driver from the ECU and place it directly in/on the coil body. The advantages of the new partitioning - e.g. no high voltage wires, reduced power dissipation on the ECU - are paid with different, mainly tougher requirements for the electronic components. By using specialized technologies for the different functions - IGBT for switching the power, SPT for protection, supply and diagnostics - in chip-on-chip technology all required functions for a decentralized ignition system can be realized in a TO220/ TO263 package.</div>
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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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.009 |
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".