Optimizing Tire Vertical Stiffness Based on Ride, Handling, Performance, and Fuel Consumption Criteria
Bibliographic record
Abstract
Researchers mostly focus on the role of suspension system characteristics on vehicle dynamics. However tire characteristics are also influential on the vehicle dynamics behavior. In this paper, the effects of tire vertical stiffness on the ride, handling, accelerating/braking performance, and fuel consumption of a vehicle are analytically investigated. Furthermore, a method for determining the optimum vertical stiffness of tires is presented. For these purposes, first an appropriate mathematical criterion for the ride, handling, accelerating/braking performance, and fuel consumption is developed. Next, to achieve the optimum tire characteristic, a performance index, which contains all of the above-mentioned criteria, is defined and optimized. In the proposed performance index, the tire vertical stiffness is a design variable and its optimization provides a compromise among ride, handling, accelerating/braking performance, and fuel consumption of the vehicle. Last, the analytical optimization results are confirmed by performing precise numerical simulations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".