Analytical Calculation of Temporal and Circumferential Orders of Radial Force Density Harmonics in External-Rotor and Internal-Rotor Switched Reluctance Machines
Bibliographic record
Abstract
This paper presents an analytical method to calculate the temporal and circumferential orders of the radial force density harmonics in switched reluctance machines (SRMs) without running the electromagnetic finite element analysis (FEA). The characteristics of the radial force density harmonics in several SRM topologies are investigated, including the 6/4, 24/16, and 6/14 internal-rotor (IR) SRMs, and 12/16 and 18/24 external-rotor (ER) SRM. The study shows that the temporal and circumferential orders of the radial force density harmonics depend on the pole configuration, the rotational directions of the rotor, the phase excitation sequence, and the rotor or stator radial force density waveform. The acoustic noise of a four-phase 8/6 internal-rotor SRM and a three-phase 12/16 external-rotor SRM was experimentally measured to validate the calculation of the temporal and circumferential orders of the radial force density harmonics. The proposed analytical method helps locate the possible radial force density harmonics of a given SRM configuration. In order to determine the dominant radial force harmonics, the proposed method should be complemented by analyzing the natural frequencies of the motor structure and the forcing frequencies of the radial force harmonics.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".