Title: An unknown input Kalman filter based component FDI algorithm and its application in automobiles

Authors: S. Mondal, G. Chakraborty, K. Bhattacharyya

Addresses: Department of Mechanical Engineering, Systems, Dynamics and Control Laboratory, Indian Institute of Technology, Kharagpur 721302, India. ' Department of Mechanical Engineering, Systems, Dynamics and Control Laboratory, Indian Institute of Technology, Kharagpur 721302, India. ' Department of Mechanical Engineering, Systems, Dynamics and Control Laboratory, Indian Institute of Technology, Kharagpur 721302, India

Abstract: An Unknown Input Kalman Filter (UIKF) based Component Fault Detection and Isolation (CFDI) technique for a dynamical system, affected by both plant and measurement noise, is presented. The Fault Detection and Isolation (FDI) algorithm, which consists of two steps, is developed with the assumption that the fault occurs in a single component of the system. In step 1, the detection of the fault and the isolation of the faulty region are achieved. In the next step, the faulty parameter is isolated from the faulty region. The method is applied on a road vehicle model to show the effectiveness of the algorithm.

Keywords: automotive fault detection; fault isolation; unknown input; Kalman filter; observability; residual; parameter isolation; road vehicles; modelling; automobile industry.

DOI: 10.1504/IJVAS.2007.016508

International Journal of Vehicle Autonomous Systems, 2007 Vol.5 No.3/4, pp.274 - 287

Available online: 03 Jan 2008 *

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