Physics-based MCT circuit model using the lumped-charge modeling approach
Bibliographic record
Abstract
This paper presents a physics-based model of metal-oxide-semiconductor (MOS) controlled thyristor (MCT) using the lumped-charge modeling technique. As a relatively new power semiconductor device, little effort has been made thus far in creating an accurate model for simulation use. The only MCT model available to date is that using two bipolar transistors-a behavioral subcircuit model. This model works well for static operation, but has limitations in predicting the dynamic behavior of the device due to the omission of the internal device physics. The use of the lumped-charge modeling technique facilitates the inclusion of internal physical processes and the structural geometry of the device into the model. As a result, this technique provides a more realistic and accurate one-dimensional (1-D) model than any other presently available. This paper presents the successful implementation of the lumped-charge approach on hybrid bipolar-MOS power devices such as the MCT. Most importantly, this model is capable of predicting some dynamic soft-switching behavior of the device, which was never realizable by any SPICE-based simulators. The developed model is thoroughly verified through Saber simulation and experimentation.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".