Radial Force Shaping for Acoustic Noise Reduction in Switched Reluctance Machines
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Robustness, simple construction, and low cost are some of the advantages of switched reluctance machines (SRMs). These are all desirable characteristics of an electric motor, especially in the automotive sector, where high-temperature and high-speed operation, and low cost are always in demand. However, the acoustic noise generation by conventionally controlled SRMs can prevent its use in applications where acoustic comfort is required. Acoustic noise is radiated by the stator frame when a vibration mode is excited by the respective spatial order at a forcing frequency that is close to the stator's modal natural frequency. The excitation surface wave is the radial force density waveform, which is a function of time and spatial position. In this paper, a phase radial force shaping method is proposed by using harmonic content analysis. A generic function for the radial force shape is identified, whose parameters are calculated by an optimization algorithm to minimize the torque ripple for a given average torque. From the phase radial force profile, a current reference is obtained. The proposed methodology is experimentally validated with a four-phase 8/6 SRM through acoustic noise measurements at different speed and load conditions.
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.
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 | 0.001 |
| 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 it