Instantaneous torque control using flux‐based commutation and phase‐torque distribution technique for SR motor EV
Bibliographic record
Abstract
Purpose The purpose of this paper is to propose a new instantaneous torque control method for switched reluctance motor (SR motor) and presents experimental data in electric vehicle (EV) application. Design/methodology/approach The proposed control method uses two kind of techniques: a flux‐based commutation technique prevents the negative phase torque always. On the other hand, a direct phase‐torque distribution technique gives suitable each phase‐torque command under limited DC voltage. These techniques can track motor torque to the command. These control schemes are implemented on a small processor and a field programmable gate array. Findings The experimental results of the EV show small torque ripple at low speed on both acceleration and regenerative braking. Changing the parameter of the current stop angle can improve torque ripple at high speed. The proposed method can effectively control motor torque. Practical implications The proposed method can reduce torque ripple but the implementation is very simple. The proposed control method can be used for any applications. So, that contributes to expand the application of SR motors. Originality/value The proposed control scheme requires just static torque curve obtain by finite element analysis or simple experiments. Complex parameters, such as nonlinear inductance, current to torque profiles, and other heuristics parameters, are not necessary. The proposed control is simple but practical.
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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 | 0.000 |
| 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".