Roll Plane Analysis of Interconnected Hydro-Pneumatic Suspension Struts
Bibliographic record
Abstract
This study presents a compact hydro-pneumatic strut design with enhanced working area to reduce the design pressure requirements for suspension applications. The two struts are interconnected in the roll plane to realize enhanced roll properties of the suspension. The feedback effects of the interconnecting pipes on the suspension stiffness and damping properties are derived and discussed. The influences of fluid compressibility on the effective ride and roll properties are also investigated. Asymmetric and variable damping valves are further introduced to realize adequately damped and soft ride, and high low speed damping in the roll mode. Fundamental properties of the proposed interconnected configurations are derived and compared with those of the unconnected struts with an anti-roll bar, in terms of suspension vertical stiffness, roll stiffness, and vertical and roll mode damping. Parametric studies are also performed to study the role of interconnecting parameters on the essential suspension properties. The results indicate that interconnected suspension with inherent enhanced roll stiffness and damping characteristics offers significant potential to improve the dynamic roll performance of heavy vehicles, while retaining soft vertical ride. The effectiveness of the proposed concept is further illustrated through simulation results attained under two different deterministic excitations.
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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 | 0.000 |
| 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 | 0.001 | 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".