Power Hardware-in-the-Loop based Emulation of an Open-Winding Permanent Magnet Machine
Bibliographic record
Abstract
Open-winding permanent magnet (PM) motors are increasingly being used in electric drive systems due to several advantages over traditional PM motors such as a wider speed range of operation, and improved fault tolerance. Novel testing techniques such as power hardware-in-the loop (PHIL) based machine emulation can be used to expedite the testing of new motor topologies such as the open-winding PM motor. This paper investigates the emulation of an open-winding PM machine. In order to control or suppress lower order harmonics resulting due to the emulated machine back-emf, current controllers are proposed in this paper. These proposed controllers, used for the driving inverter and the machine emulator, use multiple resonant controllers in combination with proportional-integral (PI) controllers to achieve control over emulated current harmonics of interest. Experimental results are presented to validate the performance of the proposed current controller and also highlight the utility of the developed machine emulator system to emulate various operating conditions of the open-winding PM machine.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".