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As emission limits become increasingly stringent and the price of gaseous fuels decreases, more emphasis is being placed on promoting gas engines. In the field of large engines for power generation, dual fuel combustion concepts that run on diesel/natural gas are particularly attractive. Knock in diesel/natural gas dual fuel engines is a well known yet not fully understood complex phenomenon that requires consideration in any attempt to increase load and efficiency. Thus combustion concept development requires a reliable yet robust methodology for detecting knock in order to ensure knock-free engine operation. Operating parameters such as rail pressure, start of injection and amount of diesel injected are the factors that influence oscillations in the in-cylinder pressure trace after the start of combustion. Oscillations in the pre-mixed combustion phase, or ringing, are caused by the rapid conversion of large parts of the injected diesel.

Virtual sensing refers to the processing of desired physical data based on measured values. Virtual sensors can be applied not only to obtain physical quantities which cannot be measured or can only be measured at an unreasonable expense but also to reduce the number of physical sensors and thus lower costs. In the field of spark ignited internal combustion engines, the virtual sensing approach may be used to predict the cylinder pressure signal (or characteristic pressure values) based on the acceleration signal of a knock sensor. This paper presents a method for obtaining the cylinder pressure signal in the high-pressure phase of an internal combustion engine based on the measured acceleration signal of a knock sensor. The approach employs a partial differential equation to represent the physical transfer function between the measured signal and the desired pressure. A procedure to fit the modeling constants is described using the example of a large gas engine.

Precise prediction of combustion parameters such as peak firing pressure (PFP) or crank angle of 50% burned mass fraction (MFB50) is essential for optimal engine control. These quantities are commonly determined from in-cylinder pressure sensor signals and are crucial to reach high efficiencies and low emissions. Highly accurate in-cylinder pressure sensors are only applied to test rig engines due to their high cost, limited durability and special installation conditions. Therefore, alternative approaches which employ virtual sensing based on signals from non-intrusive sensors retrieved from common knock sensors are of great interest. This paper presents a comprehensive comparison of selected approaches from literature, as well as adjusted or further developed methods to determine engine combustion parameters based on knock sensor signals. All methods are evaluated on three different engines and two different sensor positions.