Real Time Estimation of Combustion Indicators on a 4-Cylinder CI Turbocharged Engine Based on Instantaneous Engine Speed Measurement with Rapid Prototyping Implementation

Abstract

Abstract In the field of Internal Combustion Engines (ICEs), increasingly stricter regulations on pollutant emissions have made necessary to continuously monitor engine operation. Indeed, in order to tackle fault-induced variations in engine performance, continuous, real-time data related to the engine’s thermodynamic cycle is needed: specifically, obtaining detailed information on the engine combustion phase is paramount. Combustion indicators are calculated through in-cylinder pressure, for which both direct and indirect measurement techniques can be employed. The former are accurate, but suffer from limited durability, while the latter are less accurate, but durable and less expensive, therefore more attractive for mass production applications. A technique for reconstructing the pressure cycle of each cylinder, through the combination of instantaneous crankshaft speed signal and a 0D thermodynamic model, was developed by the authors in MATLAB-Simulink environment and validated against experimental data. The objective of the present study is to implement this model on a four-cylinders CI turbocharged engine. Specifically, since focus was put on assessing the model real-time capability, efforts were made to execute the model inside a real-time controller. The paper presents the results of the experimental campaign that was carried out to validate the developed model. The signals from the pickup wheel and the camshaft phase sensor represent the main inputs, as they allow for the calculation of the engine speed and the detection of each cylinder Firing Top Dead Center (FTDC), respectively. Pressure sensors were mounted in all the cylinders for direct pressure acquisition. Tests were carried out under different operating conditions, specifically by varying speed, load and by reproducing the effects of injector malfunction in one cylinder. The developed model proved to be sensitive to operating conditions variations, correctly calculating combustion indicators such as the Indicating Mean Effective Pressure with real-time capability.