An Improved Torque Sharing Function for Torque Ripple Reduction in Switched Reluctance Machines
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- Meta-epidemiology (narrow)
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Bench or experimentalConsensus signal: none
- Genre
- Candidate signal: EmpiricalConsensus signal: none
- Teacher disagreement score
- 0.817
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
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 | 0.001 |
| 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)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.222 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
An offline torque sharing function (TSF) is introduced in this paper for torque ripple reduction in switched reluctance machines (SRM). This TSF uses static flux linkage characteristics of the machine obtained from finite element analysis or experiments that describe the machine dynamics to determine optimal current profiles such that the torque ripple reduction is achieved with minimal copper losses. Due to this feature, the proposed TSF performs well across a wide speed range. Additionally, the objective function of the proposed TSF uses only one weight parameter, which facilitates the use of this TSF. In this paper, an intuitive justification for the selection of this weight parameter is given, and the performance of this TSF is validated in simulation and experimentally on a 5.2 kW, four phase SRM. To baseline its performance, the proposed TSF has been compared to the offline TSF in the literature, which shows that it has better current tracking performance at higher speeds due to the inclusion of flux linkage characteristics. Finally, it has been compared to conduction angle control at speeds above the base speed to show that it can be a viable alternative for the control of SRM even in an operation region normally not considered for TSF.
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.
The record
- Venue
- IEEE Transactions on Power Electronics
- Topic
- Electric Motor Design and Analysis
- Field
- Engineering
- Canadian institutions
- McMaster University
- Funders
- Canada Excellence Research Chairs, Government of CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
- Keywords
- Switched reluctance motorControl theory (sociology)TorqueTorque rippleFlux linkageRippleDirect torque controlCopper lossReduction (mathematics)Computer scienceEngineeringMathematicsPhysicsControl (management)VoltageArtificial intelligenceInduction motor
- Has abstract in OpenAlex
- yes