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Record W2780111594 · doi:10.1109/tcst.2017.2772912

Quarter-Car Experimental Study for Series Active Variable Geometry Suspension

2017· article· en· W2780111594 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2017
Typearticle
Languageen
FieldEngineering
TopicMechanical Engineering and Vibrations Research
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilChina Scholarship Council
KeywordsSeries (stratigraphy)Suspension (topology)GeometryQuarter (Canadian coin)Variable (mathematics)MathematicsWindow (computing)Computer scienceMathematical analysisGeologyGeographyPure mathematics

Abstract

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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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.825

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.267
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it