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Record W4393372097 · doi:10.1109/lra.2024.3384053

Design, Control, and Validation of a Brake-by-Wire Actuator for Scaled Electric Vehicles

2024· article· en· W4393372097 on OpenAlex
Benjamin DeBoer, Jeremy B. Kimball, Kush Bubbar

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

VenueIEEE Robotics and Automation Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicVehicle Dynamics and Control Systems
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsBrakeActuatorAutomotive engineeringControl (management)EngineeringComputer scienceControl engineeringElectrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

X-by-wire technology is revolutionizing the automotive industry, enabling the implementation of superior advanced driver assistance systems (ADAS) to augment the driving experience. For cost-effective X-by-wire ADAS module development, testing can be conducted on scaled vehicles. While drive-by-wire and steer-by-wire are simple to implement on scaled vehicles, there have been no applications of scaled brake-by-wire systems. This letter presents the design, control, and validation of a cable-driven brake-by-wire system. Implementing a series elastic actuator and modelling the brake-by-wire system with high fidelity eliminates any sensor requirements within the brake caliper, allowing brake-by-wire capability to be added without increasing the vehicle's unsprung mass. The designed system was constructed and tested to validate the proposed system model and controller, setting the groundwork for future development of brake-by-wire ADAS systems on scaled vehicles.

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 score0.843
Threshold uncertainty score0.398

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 studies0.0000.000
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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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