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Record W2102566277 · doi:10.1155/2013/893835

Stability Analysis of Vehicle Negotiating a Curve in the Plane

2013· article· en· W2102566277 on OpenAlexaff
Wencai Sun, Jingjing Tian, Shiwu Li, Zhifa Yang, Zheng-Dong Ma

Bibliographic record

VenueAdvances in Mechanical Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsMinistry of Transportation of Ontario
FundersXihua UniversityChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsChassisStability (learning theory)Nonlinear systemAutomobile handlingPhase planeVehicle dynamicsTire balancePlane (geometry)Slip angleWork (physics)InstabilityAutomotive engineeringControl theory (sociology)Computer scienceEngineeringSteering wheelStructural engineeringMathematicsMechanical engineeringPhysicsMechanicsGeometryArtificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

The steering stability of vehicle was the most important part of vehicle handling and stability. The stability analysis of vehicle negotiating a curve in the plane was studied through simulation. The vehicle dynamics model used in this paper had two degrees of freedom with nonlinear tire characteristics. When two vehicle state variables, namely, velocity and steering angle, were changed, the GA and phase space analysis were used to compute the equilibrium points and analyze the phase space characteristics of vehicle system. Considering the nonlinear tire characteristic, the working region of tire was figured out and compared, while the vehicle was under different operating conditions. From the analysis results, it could be concluded that working in the nonlinear region of tire characteristic was the ultimate reason of vehicle instability. The knowledge derived from simulation results could dramatically enhance the understanding of stability of the actual vehicle negotiating a curve on an even surface. Such knowledge was a prerequisite for robustly designing the chassis, such as steer-by-wire, which would be the topics of future work.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.197
Teacher spread0.193 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2013
Admission routes1
Has abstractyes

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