Incorporating Saturation in Permanent-Magnetic Synchronous Generator Modeling for All-Electric Ship Applications
Bibliographic record
Abstract
Increasing ship-board power demand coupled with environmental sustainability initiatives has created interest in pursuing all-electric ships (AES) for both commercial and military applications. AES can be equipped with power electronic components, loads, machines, and cables. Many electric generator topologies can be used for AES. To our best knowledge, permanent-magnetic synchronous generator (PMSG) is the most attractive solution because it is characterized by low maintenance levels, high compactness, and quiet operation. To evaluate, provide information, and guide technology selection, modeling and simulation of AES is required. This paper proposes an accurate PMSG model to analyze the dynamic characteristics of the generation system and to support system critical operations in the event of dynamic load change or component failure. Saturation in PMSG is modeled by means of analytical expressions, which can be easily embedded in equivalent-circuit models and which has some distinct advantages over look-up tables. The proposed model can be used in real-time control applications and in computer simulations. Four case studies are investigated through computer simulations with Simulink. From the simulations, it is found that the PMSG model has accurate performance as the variations of voltages and currents within acceptable ranges.
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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) | 0.000 | 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".