A Comparison of Virtual Sensors for Combustion Parameter Prediction of Gas Engines Based on Knock Sensor Signals
Precise prediction of combustion parameters such as peak firing pressure (PFP) or crank angle of 50% burned mass fraction is essential for optimal engine control. These quantities are commonly computed from in-cylinder pressure sensor signals and are crucial for high efficiencies and low emissions. Highly accurate in-cylinder pressure sensors are usually only applied to test rig engines due to their high cost, limited durability and special installation conditions. Therefore, there is great interest in alternative approaches that employ virtual sensing based on the non-intrusive sensor signals retrieved from common knock sensors. These methods are either data-driven or physics-based and have been proven to deliver an accurate prediction of the aforementioned combustion parameters. This paper presents a comprehensive comparison of selected approaches to determine engine combustion parameters based on knock sensor signals.