Virtual Sensors for Automotive Engine Sensors Fault Diagnosis in Second-Order Sliding Modes

Abstract

Automotive engine functions are entirely dependent on installed sensors performance. Any malfunction in the sensors can lead to degraded engine efficiency. This manuscript presents a novel scheme to devise virtual sensors for health monitoring of engine air intake path sensors. The proposed scheme assists in: Sensing of critical immeasurable parameters like Volumetric and Combustion efficiency, development of Virtual Sensor from manifold pressure dynamics for rotational speed and vice versa, Health Monitoring of the manifold pressure and crankshaft sensor. For the suggested scheme, two robust second-order sliding mode observers are employed that require two state mean value engine model based on inlet manifold pressure and rotational speed dynamics. The proposed methodology has the potential of online implementation on any automotive engine after minor tuning. In this paper, the procedure is customized for 1.3 L gasoline engine sensors: Manifold Pressure and Crankshaft sensor. The implementation results demonstrate that all the three mentioned tasks are accomplished efficiently.