Performance analysis and operating limits of dual inverter open winding IPMSM drives
Bibliographic record
Abstract
Operating capabilities of a dual inverter Open Winding Interior Permanent Magnet Synchronous Motor drive are investigated and compared with those of a conventional single inverter drive in Maximum Torque per Ampere and Field Weakening regions. To predict the performance and operating limits of the drive systems with improved accuracy, the impact of saturation on inductances and Permanent Magnet flux linkage values are taken into account, and core, copper, friction and windage, and solid losses (due to skin and proximity effects and magnet losses) are considered in a wide speed range. It is shown how core saturation affects the d- and q-axis inductances and saliency ratio, and electromagnetic and mechanical losses significantly change in various operating points. It is revealed how the above effects may affect the operating capability of the machine in different drive configurations. Different active and reactive power sharing assumptions are made in the dual inverter drives, and it is shown how each of the related controllers is accordingly defined. It is demonstrated that in certain operating regions of the open winding machine’s torque versus speed envelope, the original active and reactive power sharing principles and the defined controllers have to be modified, otherwise the machine may not be able to operate throughout its entire anticipated operating points. Performance prediction is conducted using machine’s electromagnetic parameters and losses that are obtained via Finite Element Analysis, coupled with an optimization algorithm to find optimal operating points in Maximum Torque Per Ampere and Field Weakening regions. The analytical findings are further validated against experimental results obtained from a 1-kW dual inverter Interior Permanent Magnet Synchronous motor drive.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".