Model-based fault-tolerant control for an automotive air suspension control system

Abstract

This paper presents a new fault-tolerant control (FTC) algorithm for an automotive air suspension control (ASC) system. The FTC algorithm proposed in this paper provides the fault detection, diagnosis, and management of a closed-loop air suspension control system. A new model-based fault detection and isolation algorithm for the height sensors, which are critical but vulnerable components of the ASC system, is also proposed. The height sensor fault is detected on the basis of the geometric relationships of the suspension and is isolated by implementing the analytical redundancy of the height sensors using roll and pitch angle estimates derived by a Kalman filter. An adaptive threshold is designed and applied in order to enhance the robustness of the fault detection and isolation against model uncertainties. The effectiveness of the proposed model-based FTC algorithm is verified via simulation and actual vehicle tests.