Model-based Sensor Fault Detection and Isolation for X-By-Wire Vehicles Using a Fuzzy Logic System with Fixed Membership Functions

In this paper, a supervisory sensor diagnostics system for x-by-wire vehicles is described. The x-by-wire vehicle has brake-by-wire as well as front and rear steer-by- wire subsystems. A detailed discussion of a model-based diagnostics approach that is used for detecting, as well as determining the location and type of sensor faults is given. The sensors under study are vehicle front and rear road wheel angles, lateral acceleration, yaw rate and four wheel speeds. A multi-model-based methodology is utilized for estimation of yaw rate, lateral acceleration and road wheel angle signals. Three estimates of the vehicle system behavior are generated and compared to the actual measurements. The differences between the measurements and the estimates are used to generate four residuals. Fuzzy membership functions for each of the residuals are defined and the degree-of-membership of the residuals is continuously evaluated. Fuzzy rules are developed and used to detect, isolate and determine the fault type. Specific patterns are used to detect and identify the location and type of sensors faults. The fuzzy rules implement the fault-symptoms relationships. The output of the fuzzy reasoning system is a crisp number, according to Sugeno fuzzy system, that can be interpreted as the probability of the occurrence of a specific fault.