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).
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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.
