Improved Predictive Equations for Cetane Number

Three new predictive equations for cetane number have been developed Each of these equations is shown to be superior to the current cetane index equation (ASTMD976-80) for a large fuel data base.One of the equations has the further advantage of requiring only one property measurement (aniline point). The equations were developed from a detailed analysis of functional relationships between measured cetane number (ASTM D 613-84) and commonly measured physical properties of diesel fuels: aniline point, density, and distillation temperatures. The data base for this study totaled 1229 fuels, including commercial fuels from the U.S., Canada, Europe, and Japan, synthetic fuels derived from tar sands, shale, and coal; and a diversity of research fuels blended from straight-run and cracked stocks. The equations were optimized using data-fitting techniques which account for bias amongst the various data sources and for measurement errors in both the dependent and independent variables.