MétaCan
Menu
Back to cohort
Record W2094247368 · doi:10.1243/0954407011528176

Sensitivity of rearward amplication control of a truck/full trailer to tyre cornering stiffness variations

2001· article· en· W2094247368 on OpenAlexaff
M. EI-Gindy, Nezih Mrad, Xiaohua Tong

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · 2001
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsYawControl theory (sociology)TrailerController (irrigation)AxleTruckSensitivity (control systems)Automotive engineeringAutomobile handlingEngineeringTorqueVehicle dynamicsAccelerationArticulated vehicleStiffnessComputer scienceControl (management)Structural engineering

Abstract

fetched live from OpenAlex

Highway safety and vehicle performance are two important considerations in the design of a heavy vehicle combination. In this paper a performance measure called the ‘rearward amplification ratio’ (RWA) is used as a control criterion in the design of a vehicle-handling controller. This approach is different to conventional control techniques. The RWA is defined as the ratio of the peak lateral acceleration at the rearmost trailer's centre of gravity (CG) to that of the lead unit during a lane-change manoeuvre. The vehicle under consideration is a six-axle truck/full trailer, which usually exhibits a high level of RWA leading to roll-over during obstacle avoidance manoeuvres. In this study, several control strategies are examined, namely active yaw control at the truck CG, active yaw control at the dolly CG and active yaw control at the trailer CG. These could be employed individually or in combination. The effect of an active control torque applied to various vehicle units is examined by using an optimal linear quadratic regulator approach combined with a simplified four degrees-of-freedom linear vehicle model. The controller performance index parameters are determined for the vehicle based on acceptable RWA target values. The sensitivity of the controller to tyre cornering stiffness variation is further evaluated. Simulation results indicate that the RWA can be reduced without significant change of the uncontrolled vehicle trajectory when active yaw torque is applied to the dolly. The controller can be more effective in improving the dynamic performance and roll stability of this type of commercial vehicle, if applied to the lead unit (truck) or to the last unit (trailer). However, the path of the vehicle will be strongly influenced and driving difficulties can be experienced. For active yaw control at the dolly CG, the optimal controller is found to be most sensitive to the dolly's tyres' cornering stiffness variations and least sensitive to steering axle from the RWA point of view. It is also found that the controller is most sensitive to steering axle parameter variations for path following.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.006
GPT teacher head0.192
Teacher spread0.185 · 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

Citations41
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part D Journal of Automobile EngineeringSame topicVehicle Dynamics and Control SystemsFrench-language works237,207