Search Results

Model-based analysis of in-cylinder pressure sensor signals has been a key component for internal combustion engine research, diagnostics and controller development during the past decades. This analysis is often based on simple thermodynamic models of the in-cylinder processes. In order for the analysis to give accurate results, the models need to be sufficiently calibrated. This paper investigates the use of the extended Kalman filter and the particle filter for the purpose of online estimation of top-dead-center offset, a convective heat-transfer coefficient and cylinder-wall temperature in a Gatowski heat-release model. Simulation results show that the filters are consistent in estimating the true parameters, that the assumed model uncertainty and heat-release noise density works as filter tuning parameters. The filters were found to be sensitive to errors on pressure-sensor offset and the cylinder compression ratio.

Observations from engine experiments indicates that the gross indicated efficiency (GIE) increases when the inlet temperature (Tinlet) is lowered. The change in Tinlet affects several important factors, such as the heat release profile (affecting heat and exhaust losses), working fluid properties, combustion efficiency and heat transfer losses. These factors all individually contributes to the resulting change in GIE. However, due to their strong dependency to temperature it is not possible to quantify the contribution from each of these parameters individually. Therefore, a simulation model in GT-power has been created and calibrated to the performed engine experiments. With simulations the temperature dependency can be separated and it becomes possible to evaluate the contribution to GIE from each factor individually. The simulation results indicate that the specific heats of the working medium are the largest contributor.