Torque Ripple Reduction in Brushless DC Motors with 180° Commutation
Bibliographic record
Abstract
Hall-sensor-based brushless DC (BLDC) motors are utilized extensively in low-cost applications due to their manufacturing simplicity and ease of control. Often, BLDC motors are controlled using the 120° commutation logic, which naturally approximates the maximum torque per ampere (MTPA) operation. However, in some applications, the 180° commutation is preferred since it allows higher DC voltage utilization and continuous phase currents, although it comes at the cost of higher torque ripple. This paper proposes a new torque control strategy to reduce the torque ripple in the 180°-commutated BLDC motors. The proposed method dynamically adjusts the duty cycle within each switching interval based on the reference, the estimated electromagnetic torque, and the derivative of the torque. The proposed method is analyzed under different speeds and back EMF shapes, and its effectiveness is validated through simulation and experimental results on a typical industrial BLDC motor.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".