Quarter-Car Experimental Study for Series Active Variable Geometry Suspension
Bibliographic record
Abstract
In this paper, the recently introduced series active variable geometry suspension (SAVGS) for road vehicles is experimentally studied. A realistic quarter-car test rig equipped with double-wishbone suspension is designed and built to mimic an actual grand tourer real axle, with a single-link variant of the SAVGS and a road excitation mechanism implemented. A linear equivalent modeling method is adopted to synthesize an H-infinity control scheme for the SAVGS, with the geometric nonlinearity compensated. Simulations with a theoretical nonlinear quarter-car indicate the SAVGS potential to enhance suspension performance, in terms of ride comfort and road holding. Practical features in the test rig are further considered and included in the nonlinear model to compensate the difference between the theoretical and testing behaviors. Experiments with a sinusoidal road, a smoothed bump and hole, and a random road are performed to evaluate the SAVGS practical feasibility and performance improvement, the accuracy of the model, and the robustness of the control schemes. Compared with the conventional passive suspension, ride comfort improvements of up to 41% without any deterioration of the suspension deflection are demonstrated, while the SAVGS actuator power is kept very low, at levels below 500 W.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".