Tesfa, Belachew, Mishra, Rakesh, Zhang, Cuiping, Gu, Fengshou and Ball, Andrew (2011) NOx Prediction Based on Cylinder Pressure Measurement for Engine Emission Monitoring. In: Proceedings of the 24th International Congress on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2011). COMADEM, pp. 1330-1340. ISBN 0954130723Metadata only available from this repository.
Meeting European NOx emission standards is one of the biggest challenges facing automotive industries. The available technologies to measure NOx emission are dependent on measurement of different NOx species. In addition, in most cases it requires conversion of other NOx species to NO for measurement purposes. The ability to measure NOx emission on-line during the transient engine operation may be very difficult due to the delay in reaction time in the NOx measuring apparatus. NOx emissions in compression ignition (CI) engines are largely a thermal phenomena thus
cylinder pressure is key to making accurate predictions of NOx. If cylinder pressure data
is available the heat release during combustion can be modeled and thus NOx emission can be more accurately simulated. Therefore, the main objective of this study is to investigate the performance of the cylinder pressure in predicting the NOx emission from a CI engine running with biodiesel during both steady and transient operations. To address the problem experimental work has been conducted on a four-cylinder, fourstroke, direct injection (DI) and turbocharged diesel engine. In this investigation,
biodiesel (produced from the rapeseed oil by transesterfication process) has been used.
During the experiment the in-cylinder pressure, TDC mark, fuel flow rate, air flow rate and the NOx emission were measured. The temperature within the cylinder was predicted using the cylinder pressure. Using the temperature values the NOx emission was simulated in Zeldovich extended mechanism. The measured and simulation results of NOx emission were compared during steady state conditions and shows maximum error of 4.5%.
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