Salehi, Rasoul (Sharif University of Technology), Shahbakhti, Mahdi (Michigan Technological University), Alasty, Aria (Sharif University of Technology), Vossoughi, Gholamreza (Sharif University of Technology)

On-Line Fault Detection and Isolation (FDI) for the Exhaust Path of a Turbocharged SI Engine

Scheduled for presentation during the Contributed session "Automotive Control Systems" (TuBT1), Tuesday, October 22, 2013, 14:10−14:30, Paul Brest East

6th Annual Dynamic Systems and Control Conference, October 21-23, 2020, Stanford University, Munger Center, Palo Alto, CA

This information is tentative and subject to change. Compiled on April 24, 2024

Abstract

Detection and isolation of faults in the exhaust gas path of a turbocharged spark ignition (SI) engine is an essential part of the engine control unit (ECU) strategies to minimize exhaust emission and ensure safe operation of a turbocharger. This paper proposes a novel physics-based strategy to detect and isolate an exhaust manifold leakage and a closed-stuck wastegate fault. The strategy is based on a globally optimal parameter estimation algorithm which detects an effective hole area in the exhaust manifold. The estimation algorithm requires prediction of the exhaust manifold’s input and output flows. The input flow is predicted by a nonlinear Luenberger observer which is analytically shown to be robust to the faults in the exhaust manifold. The output flow of the exhaust manifold is detected by a sliding mode observer. The designed fault diagnosis and isolation (FDI) strategy is tested with the experimental data collected from a 1.7-liter turbocharged SI engine. The validation results show that the FDI strategy can detect a leakage fault from a 5mm hole in the exhaust manifold, and can identify the wastegate stuck faults.