A Model-Based Fault Diagnosis System for Electro-Hydraulic Brake

Huh, Kunsoo; Han, Kyutae; Hong, Daegun; Kim, Joogon; Kang, Hyoun Woo; Yoon, Paljoo

doi:10.4271/2008-01-1225

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…Physical models use models of the physical world, such as the laws of mechanics, electomagnetics, or chemical kinetics to model system behavior and to determine when anomalous behavior is present. They typically model continuous cyberphysical systems in industrial, automotive and aerospace domains whose physics are well understood, e.g, powertrain [62] and chassis systems [33] in cars. These systems run in a closed-loop, where sensors monitor the system output, then feed the data into a controller that signals actuators to adjust control as necessary to maintain the desired system output.…”

Section: Types Of Model-based Techniquesmentioning

confidence: 99%

“…They use ONAs to describe fault patterns that discriminate between different types of faults, i.e., wearouts, massive transient faults, and connector faults in automotive systems. Other diagnosis techniques for embedded systems rely on physical models to diagnose problems in powertrain [62] and chassis systems such as braking [33] in cars.…”

Section: Embedded Systemsmentioning

confidence: 99%

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Failure Diagnosis of Complex Systems

Kavulya

Joshi

Giandomenico

et al. 2012

Resilience Assessment and Evaluation of Computing Systems

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Failure diagnosis is the process of identifying the causes of impairment in a system's function based on observable symptoms, i.e., determining which fault led to an observed failure. Since multiple faults can often lead to very similar symptoms, failure diagnosis is often the first line of defense when things go wrong -a prerequisite before any corrective actions can be undertaken. The results of diagnosis also provide data about a system's operational fault profile for use in offline resilience evaluation. While diagnosis has historically been a largely manual process requiring significant human input, techniques to automate as much of the process as possible have significantly grown in importance in many industries including telecommunications, internet services, automotive systems, and aerospace. This chapter presents a survey of automated failure diagnosis techniques including both model-based and model-free approaches. Industrial applications of these techniques in the above domains are presented, and finally, future trends and open challenges in the field are discussed.

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Section: Types Of Model-based Techniquesmentioning

confidence: 99%

Section: Embedded Systemsmentioning

confidence: 99%

Failure Diagnosis of Complex Systems

Kavulya

Joshi

Giandomenico

et al. 2012

Resilience Assessment and Evaluation of Computing Systems

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“…As a transitional product between the traditional brake system and brake-by-wire system, electronic hydraulic brake has attracted much attention from the automobile component manufacturers [3,4]. EHB has eliminated the coupled relationship between the brake pedal and the driver without vacuum booster [5] which makes friction brake more simple and compact [6,7]. EHB can also control braking force of each wheel separately and realize the maximization of the braking energy recovery easily.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Coupling Characteristics Analysis of Integrated System of Electromagnetic Brake and Frictional Brake of Car

2015

Mathematical Problems in Engineering

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Since theoretical guidance is lacking in the design and control of the integrated system of electromagnetic brake and frictional brake, this paper aims to solve this problem and explores the nonlinear coupling characteristics and dynamic characteristics of the integrated system of electromagnetic brake and frictional brake. This paper uses the power bond graph method to establish nonlinear coupling mathematical model of the integrated system of electromagnetic brake and frictional brake and conducts the contrastive analysis on the dynamic characteristics based on this mathematical model. Meanwhile, the accuracy of the nonlinear coupling mathematical model proposed above is verified on the hardware in the loop simulation platform, and nonlinear coupling characteristics of the integrated system are also analyzed through experiments.

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