Novel Methodology for Integrated Actuator and Sensors Fault Detection and Estimation in an Active Suspension System

Abstract

In recent years, there has been a great deal of interest in the development of fault detection and isolation (FDI) techniques because they have been found to be important in road transport systems to ensure safe operation, reliability, and maintainability. Active suspension systems (ASSs) play an important role in passengers vehicles, especially in autonomous vehicles, because they can adapt based on the information provided by on-board sensors, thereby improving passengers' comfort and safety. However, the possible occurrence of faults in critical components, such as actuators and sensors requires robust fault diagnosis schemes to ensure good system performance and reliability. Numerous investigations exist on identification and estimation of sensor and actuator faults in ASSs, but faults in both types of components are never considered. This article proposes a new fault diagnosis scheme that allows integrated detection and estimation of actuator and sensors faults in ASSs. The proposed methodology uses two unknown input observers (UIOs) to estimate actuator faults and sensor faults separately. To avoid coupling between the estimations, it is also proposed a switch OFF mechanism for the actuator so that the coupled deflection sensor and actuator faults can be distinguished and isolated. Finally, signal flags are generated to distinguish the faulty suspension component and refine the UIO estimations.