Enhancing internal combustion engine fault detection through co-simulation with piezoelectric pressure measuring chains

Abstract

This study undertakes a proof-of-concept investigation,employing a combination of physics-based and empirical models toanalyze an in-cylinder pressure piezo-electric measurement chain. Theprimary objective is to systematically characterize and comprehenddeviations arising from the components within the measuring chain. Themethod implemented elucidates the real-time capabilities of the measuringchain model, thereby refining raw measurement data to discern deviations(errors) in the measuring chain components. This endeavor is gearedtowards facilitating effective condition monitoring and enhancing systemreliability. We detail our approach, which integrates co-simulationtechniques with piezo-electric pressure measuring chains, to detect andmitigate faults within internal combustion engines. Through this approach,we develop a comprehensive understanding of the underlying dynamics ofthe measuring chain, allowing for automated parameter estimation usinggenetic algorithms. Our key findings reveal significant improvements infault detection accuracy, with a notable reduction in in-cylinder pressureerrors. This study not only contributes to advancing fault detectionmethodologies but also holds promise for optimizing engine performanceand reliability in various applications.