2018
DOI: 10.3390/s18124468
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Model-Based Fault Diagnosis of an Anti-Lock Braking System via Structural Analysis

Abstract: The anti-lock braking system (ABS) is an essential part in ensuring safe driving in vehicles. The Security of onboard safety systems is very important. In order to monitor the functions of ABS and avoid any malfunction, a model-based methodology with respect to structural analysis is employed in this paper to achieve an efficient fault detection and identification (FDI) system design. The analysis involves five essential steps of SA applied to ABS, which includes critical faults analysis, fault modelling, faul… Show more

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Cited by 13 publications
(6 citation statements)
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“…The following charts (Fig. [16][17][18][19] show the impact of changes in selected vehicle parameters on the angular velocity of the body (  α 1 ). Simulations were made for the Opel Astra G. One parameter was changed in each case.…”
Section: Impact Of Selected Vehicle Parameters On Simulation Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The following charts (Fig. [16][17][18][19] show the impact of changes in selected vehicle parameters on the angular velocity of the body (  α 1 ). Simulations were made for the Opel Astra G. One parameter was changed in each case.…”
Section: Impact Of Selected Vehicle Parameters On Simulation Resultsmentioning
confidence: 99%
“…Assessment of the efficiency of these sensors during the vehicle service life is therefore important from the point of view of road safety. Thus, in last years there are papers deal with sensors diagnosis and estimation their bias under normal driving conditions [16,17,18]. Considering the fact that the role of mechatronic systems in vehicles is growing very rapidly, it seems natural to state that periodic testing of vehicles should carefully take into account the control of these elements.…”
Section: Introductionmentioning
confidence: 99%
“…Fault diagnosis methods can be divided into model-based (Chen et al 2018), knowledge-based (Luo et al 2018) and data-based (Onel et al 2018), among which data-based methods are common. Most of the existing data-driven fault diagnosis methods are based on the analysis of explicit variables.…”
Section: Introductionmentioning
confidence: 99%
“…Studies on fault or anomaly detection for vehicle powertrains have been carried out by various approaches. They can be classified by rule-based methods [6][7][8][9][10][11][12], mathematical 2 of 21 model-based methods [13][14][15][16][17][18][19][20][21][22][23][24][25][26], and data-driven methods that use signal processing or machine learning [27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43].…”
Section: Introductionmentioning
confidence: 99%