Fault detection and isolation has become one of the most important aspects in vehicle control system design. In this paper, we present a technique for single sensor fault detection and isolation in automotive on-board applications. It combines model-based diagnostics and a qualitative modeling approach. The proposed method is appealing as it shifts the computational effort from on-line to off-line, making the algorithm suitable for low-cost real-time applications. The methodology can be cast in the framework of discrete-event fault diagnosis. A depth one transition relation algorithm for qualitative identification which guarantees completeness is developed and applied to a 3-degree-of-freedom (DOF) nonlinear vehicle model. The paper concludes with preliminary simulation results showing the effectiveness of the proposed scheme.

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