Cycle-By-Cycle Variation in Spark Ignition Internal Combustion Engines

Download or read book Cycle-By-Cycle Variation in Spark Ignition Internal Combustion Engines written by and published by . This book was released on 1999 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary objective of this work was to extend the engine cycle simulation used by the Oxford Internal Combustion Engine Group to enable it to perform cycle-by-cycle modelling. A literature review concluded that the most appropriate metric for quantifying the cyclic variation was the coefficient of variation of the indicated mean effective pressure, and that for zero dimensional computer simulations, the most sensible parameter to perturb for cycle-by-cycle modelling was the burn rate. Modelling attempts using burn rate information alone resulted in an under-prediction of the cyclic variability exhibited by the engine. The work then examined a two-zone polytropic process model in an attempt to improve burn rate estimation. The model proved unreliable for burn rate calculations. The Rassweiler and Withrow method was then modified to include both the compression and expansion indices throughout the combustion period. The technique proved viable, but was not used because the slow burn up of the significant crevice mass in the experimental engine made calculation of an accurate expansion index doubtful. A further cause of the under-prediction in cyclic variability was postulated to be incomplete combustion, which is not detected by the burn rate model. A completeness of combustion parameter was derived from information contained in the Rassweiler and Withrow analysis. This parameter was used along with burn rate variations to perturb the cycle simulation and resulted in good cycle-by-cycle agreement between the experimental data and the modelled data in terms of mean effective pressure, maximum pressure, and the phasing of maximum pressure. Cyclic measurements of NO showed that the technique did not predict the cyclic variability in NO formation, and this was attributed to the sensitivity of NO formation to parameters that were not allowed to vary on a cyclic basis within the model (such as residuals).