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Record W2098096725 · doi:10.1177/0959651813497667

Integrated momentum wheel and differential braking control to improve vehicle dynamic performance

2013· article· en· W2098096725 on OpenAlex
Fereydoon Diba, Ebrahim Esmailzadeh

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsYawAutomotive engineeringMoment (physics)Vehicle dynamicsEngineeringDifferential (mechanical device)Control theory (sociology)Electronic brakeforce distributionControl (management)Computer scienceBraking systemBrakePhysicsAerospace engineering

Abstract

fetched live from OpenAlex

Recent studies showed that active yaw moment control is the most effective method to improve the stability and road handling of vehicles. Corrective yaw moment action should be applied to a vehicle in order to improve the vehicle dynamic performance. The corrective yaw moment is directly related to the interaction between the tires and road, which could either be generated directly or indirectly. Subsequently, the performance of the yaw moment control system, in low-friction road conditions, would noticeably be reduced. An innovative method is proposed to generate the corrective yaw moment by utilizing a momentum wheel that works independent of the tire/road interaction. A comprehensive dynamic analysis of this model, when is integrated with a direct yaw moment control system, has been carried out. Computer simulation results for the vehicle model combined with an integrated momentum wheel and differential braking, under different road conditions, are presented.

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: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

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

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 head0.003
GPT teacher head0.158
Teacher spread0.155 · 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