Fuzzy logic method for the prediction of cetane number using carbon number, double bounds, iodic, and saponification values of biodiesel fuels

The aim of present study is to develop an accessible accurate estimation of CN based on fatty acid methyl esters and to provide a proper solution for presenting a user-friendly method. In fact, this study calculates the density, viscosity, and HHV based on FAMEs and predicts the CN by employing fuzzy method within a set. This is an interesting approach that has not been used in similar articles. Gaussian membership functions with 81 roles were employed to develop the fuzzy model. The model was developed based on Carbon number, Double bond, Saponification number, and Iodine value to predict the CN. Performance factors of r, RMSE, MAE, and R-2 were calculated as 0.9912, 1.0723, 0.63427, and 0.9828, respectively to predict the CN. The results of FAMEs effect on properties of biodiesel showed, increasing Carbon number of FAMEs increases the CN, viscosity, and HHV, but increasing the number of Double bonds decreases CN, viscosity, and HHV. While the effect of increasing Carbon number of FAMEs on density was vice versa. Based on results, C16:00, C18:00, C18:1, and C18:02 FAMEs are approximately in components of all conventional oils; therefore, they can be effective on physical properties of biodiesels. (c) 2019 American Institute of Chemical Engineers Environ Prog, 38: 584-599, 2019