A VBR induction machine model implementation for SimPowerSystem toolbox in Matlab-Simulink
Bibliographic record
Abstract
This paper presents a Voltage-Behind-Reactance (VBR) induction machine model for the Matlab-Simulink toolbox SimPowerSystem, which is widely used for simulations of power and power electronics systems. In the proposed VBR model, the three-phase stator branches are represented by decoupled and constant R-L branches behind voltage sources, which provide a direct interface of the model with the external network-circuit. The rotor subsystem is expressed in the qd coordinates resulting in a high numerical efficiency. The VBR model has full-order and is otherwise algebraically equivalent to the classical qd model. We present case studies of induction machine interfaced with resistive and inductive networks. The studies show that the proposed model significantly improves the machine-network interface and enhances the numerical accuracy and efficiency as compared with the built-in SimPowerSystem qd machine model for the discretized solution of electrical circuit.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.010 |
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".