Sensitivity of Steering Wheel Nibble to Suspension Parameters, Tire Dynamics, and Brake Judder
Bibliographic record
Abstract
This paper presents a unified framework for addressing NVH related issues attributed to tire uniformity and Brake rotor DTV. While the focus is on the perceptible manifestation of such vibration (nibble), the presentation goes to the root-cause of nibble and how various suspension/tire/brake components contribute to the generation/amplification of such vibration. While the tire/brake excitation mechanisms have different origins, they cause the same (nibble) symptom to the driver. Results are presented for three types of vehicle suspensions, along with procedures that were developed specifically for this study and some of the understanding that was gained.. Also presented is an efficient data reduction scheme that makes it easy to visualize 3D motions of suspension components and investigate their dynamics. Amongst the “take-aways” from this study are 1) an understanding of how tire/brake excitation causes nibble, 2) an overview of the various parameters influencing nibble sensitivity, and 3) How this information can be used to alter the NVH attributes of a given vehicle.
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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 | 0.004 |
| 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) | 0.002 | 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".