Comprehensive Analysis and Optimized Control of Torque Ripple and Power Factor in a Three-Phase Mutually Coupled Switched Reluctance Motor With Sinusoidal Current Excitation
Bibliographic record
Abstract
This article presents a comprehensive analysis of torque ripple and power factor for three-phase mutually coupled switched reluctance motors (MCSRMs) with sinusoidal current excitation. MCSRMs controlled by sinusoidal currents have the advantage of using the conventional voltage source inverter and the conventional vector control. However, MCSRMs are characterized by high torque ripple and low power factor. The torque harmonics due to the sinusoidal current excitation are investigated, and the effect of the current excitation angle on the motor saturation level and the power factor is analyzed. These analyses are then used in the development of an optimized control method to reduce torque ripple and to increase power factor and average torque. In the proposed control method, the power factor and phase voltage are calculated by the knowledge of the phase flux linkage and phase current. The phase flux linkage is represented in terms of Fourier coefficients, where these coefficients are functions of direct- and quadrature-axis currents. Hence, they are estimated from 2-D lookup tables (LUTs), which are independent of rotor position. Similarly, the Fourier coefficients of the torque harmonics are also estimated from the 2-D LUTs. The independence of the LUTs from rotor position reduces the size of the LUTs significantly. The proposed control method is validated by experiments on a 2-kW 12/8 MCSRM.
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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 | 0.000 | 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 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".