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Development of an on-line model to predict the in-cylinder residual gas fraction by using the measured intake/exhaust and cylinder pressures
Authors:S Choi  M Ki  K Min
Institution:(1) Department of Bioengineering, Imperial College, London, UK
Abstract:The in-cylinder RGF (residual gas fraction) of internal combustion engines for new combustion concepts, such as CAI (controlled auto ignition) or HCCI (homogenous charged compression ignition), is a major parameter that affects the combustion characteristics. Thus, measurement or prediction of the cycle-by-cycle RGF and investigation into the relation between the RGF and the combustion phenomena are critical issues. However, on-line prediction of the cycle-by-cycle RGF during engine testing is not always practical due to the requirement of expensive, fast response exhaust-gas analyzers and/or theoretical models that are just too slow for application. In this study, an on-line model that can predict the RGF of each engine cycle and cylinder during the experiment in the test cell has been developed. This enhanced model can predict the in-cylinder charge conditions of each engine cycle during the test in three seconds by using the measured dynamic pressures of the intake, exhaust, and cylinder as the boundary conditions. A Fortran77 code was generated to solve the 1-D MOC (method of characteristics). This code was linked to Labview DAQ as a form of DLL (dynamic link library) to obtain three boundary pressures for each cycle. The model was verified at various speeds and valve timings under the CAI mode by comparing the results with those of the commercial code, GT-Power.
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