A Simple Large Signal Model for Isolated DC-DC Converters
Bibliographic record
Abstract
In this paper, a large signal model for isolated DC-DC converters is proposed. The model is applicable to both current and voltage mode control. The model has the principle advantage that it is simple to derive-it takes the same form as the switching converter that it is derived from. In the model, the MOSFET switches are replaced by dependent current and voltage sources equal to the average current through the switch, or average voltage across the switch. The active switch and its corresponding synchronous rectifier are replaced by dependent average current sources. In multiple switch topologies, the additional switches are replaced by dependent average voltage sources. Implementation of the model is very simple since no mathematical derivations are required. The only change to the circuit is the replacement of the switches by their dependent sources. The model is simple to implement in circuit simulation software packages such as SPICE. Once implemented, small signal and large signal behaviour can be obtained through simulation. The model is verified experimentally for the small signal and large signal cases using a prototype of the asymmetrical half-bridge topology operating at 48 V input, and 5 V at 6 A load and a 400 kHz switching frequency. Good agreement is obtained between the simulation and experimental results validating the model
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".