Experimental investigation of active yaw moment control system using a momentum wheel
Bibliographic record
Abstract
Active yaw moment control is one of the most effective methods to improve the lateral stability and safety of vehicle. In this method, the overall yaw moment of the vehicle is modified by applying the corrective yaw moment generated by the systems that are mostly dependent on the tyre and road interaction. A unique technique to generate the corrective yaw moment has been considered and experimentally analysed in this work. This system utilizes a momentum wheel to generate the corrective yaw moment, which is independent of the tyre/road interaction, and is not limited by the adhesion between the tyre and road. A prototype model has been designed and developed to conduct the experimental tests and also to analyse the vehicle dynamics responses and examine the effectiveness of the designed controller. A microcontroller along with the essential sensors has been employed in the prototype to execute the embedded control system, which consists of the control algorithms, states estimator and the Kalman filter. This system provides a better vehicle performance and improves the responses of vehicle on low-friction roads. Experimental results also confirmed that the momentum wheel performance is not limited by the tyre/road adhesion condition.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".