optimized Switching Angle-based Torque Control of Switched Reluctance Machines for Electric Vehicles
Bibliographic record
Abstract
This paper presents an optimized switching angle-based combined torque control method for switched reluctance machines (SRMs) in electric vehicles. Below the base speed, the direct instantaneous torque control (DITC) method is employed to reduce the torque ripple, while the average torque control (ATC) method is used above the base speed. Considering the fuel economy and ride quality of an electric vehicle, efficiency and torque performance is enhanced by turn-on and turn-off angle optimization. A system-level vehicle model is used to compare the battery state-of-charge (SOC) and torque ripple between the optimized switching angles and the fixed angles on a test drive cycle. The simulation results show that the proposed method saves 0.19 kWh of energy over 3.8 kWh consumption (5%) and generates 9% less torque ripple in the combined test cycle.
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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) | 0.000 | 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 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".