An Unknown Input Observer for Fault Detection Based on Sliding Mode Observer in Electrical Steering Assist Systems

Steering assist system controls the force transfer behavior of the steering system and improves the steering probability of the vehicle. Moreover, it is an interface between the diver and vehicle. Fault detection in electrical assisted steering systems is a challenging problem due to frequently use of these systems. This paper addresses the fault detection and reconstruction in automotive electrical steering assist systems. Two types of faults including sensor fault and actuator fault are investigated. In this paper, four different model-based fault detection methods including Luenberger observer method, Parity space method, decoupling filter of fault from disturbance method and the unknown input observer are studied. In each method, a sensor and actuator fault is investigated based on the model of the system. Moreover, we examine a method for the fault reconstruction based on the sliding mode observer. Finally, these methods are applied to an automotive electrical steering assist system. The results are presented and thoroughly discussed.