Wheel Drive Unit Lift Corrections in Automotive Wind Tunnels
Bibliographic record
Abstract
Correct simulations of rotating wheels are essential for accurate aerodynamic investigations of passenger vehicles. Therefore, modern automotive wind tunnels are equipped with five-belt moving ground systems with wheel drive units (WDUs) connected to the underfloor balance. The pressure distribution on the exposed areas of the WDU belts results in undesired lift forces being measured which must be considered to obtain accurate lift values for the vehicle. This work investigates the parasitic WDU lift for various configurations of a crossover SUV using numerical simulations that have been correlated to wind tunnel data. Several parameters were considered in the investigation, such as WDU size, WDU placement, tyre variants and vehicle configurations. The results show that the parasitic lift is more sensitive to the width than the length of the WDU. However, the belt length is also important to consider, especially if the wheel cannot be placed centred. Varying the tyre pattern changes the parasitic lift and the effect is coupled to the rim design. The lift correction reduces for wider tyres, as there is less exposed belt area. Modifying the tyre shoulder and sidewall geometry or considering different vehicle configurations only results in minor differences. Finally, fitting the same wheels to a different vehicle, causes deviations only at the rear wheels due to differences in the shielding from the front wheel wake. Generally, the largest differences in parasitic lift occur when there is a shift in the balance between the inner and outer low-pressure zones at the upstream tyre shoulders. In this work, such changes are observed when there is a considerable alteration of the separation point on the tyre shoulder or the amount of outwash from the wheel wake.
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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 | 0.002 |
| 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) | 0.001 | 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".