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General Information
    • ISSN: 2010-3697
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET).
    • E-mail ijmo@iacsitp.com
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2014Vol.4(4): 342-345 ISSN: 2010-3697
DOI: 10.7763/IJMO.2014.V4.397

Research of Fault Detection and Diagnosis for EMB Sensors System Based on Particle Filter

C. Y. Li and Y. N. Xu
Abstract—The electro-mechanical-brake (EMB) system which influences safety and reliability of a pure electric vehicle has received much attention. In EMB system, the feedback sensor signals enhance the accuracy of a pure electric vehicle brake. According to EMB sensor faults, the EMB mathematical model is established based on brushless DC motor (BLDCM). It provides analytical signals for a motor current, a motor speed, and a braking force to an EMB controller. Considering nonlinear characteristics of the EMB system, an observer is designed based on particle filter (PF) algorithm. Then, a sensor state and a fault can be directly estimated by this observer. Also, the residual is used for the sensor faults detection. The simulation result shows that when a sensor has a fault, the designed particle filter not only detects the fault in real-time, but also can locate the fault sensor accurately. The proposed method is proofed feasible and effective.

Index Terms—Electro-mechanical brake, fault detection, particle filter, sensor fault.

The authors are with the division of electronic and communication engineering of Yanbian University, Yanji, China (e-mail: 2013050233@ybu.edu.cn, ynxu*@ybu.edu.cn).


Cite: C. Y. Li and Y. N. Xu, "Research of Fault Detection and Diagnosis for EMB Sensors System Based on Particle Filter," International Journal of Modeling and Optimization vol. 4, no. 4, pp. 342-345, 2014.

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