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Record W2735445600 · doi:10.1177/0954407017713103

Design and optimization of a cam-actuated electrohydraulic brake system

2017· article· en· W2735445600 on OpenAlexaff
Laaleh Durali, Amir Khajepour, Soo Jeon

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBrakeAutomotive engineeringAutomotive industryHydraulic brakeMechanism (biology)Brake padEngineeringTorqueComponent (thermodynamics)Disc brakeMechanical engineeringControl engineeringComputer science

Abstract

fetched live from OpenAlex

Although different types of brake-by-wire mechanism including electrohydraulic brakes, electromechanical brakes, electronic wedge brakes and distributed electrohydraulic brakes have been developed in the past two decades, there is still an increasing demand for further improvement and also for development of new brake mechanisms in the automotive industry because of the escalating requirements for higher safety and better performance. This paper proposes a novel brake-by-wire system based on the cam actuation mechanism. The proposed cam-actuated electrohydraulic brake system is a combination of an electrical component, a mechanical component and a hydraulic component. The unique feature of the proposed cam-actuated electrohydraulic brake system is that the characteristics of the motor torque amplification can be optimized by careful design of the cam shape. The overall structure of the cam-actuated electrohydraulic brake system is described, and the dynamic model of the system is developed. Optimum design of the cam-actuated electrohydraulic brake system is obtained by multi-objective optimization, and the obtained simulation results are discussed. The compactness and the self-contained characteristics of the design enable the brake system to be installed on each wheel, allowing fully independent control of each wheel for better stability control.

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 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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.715
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.196
Teacher spread0.187 · 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 teacher head, 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

Citations16
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part D Journal of Automobile EngineeringSame topicHydraulic and Pneumatic SystemsFrench-language works237,207