Multivariate statistical optimization of the ethanol fuel dehydration process using ionic liquids

Abstract

In this work, the ethanol fuel dehydration process was optimized using the Aspen Plus? simulator and a multivariate statistical technique based on the desirability function. The suitability of the ionic liquids 1-methylimidazolium chloride ([Mim][Cl]), 1-ethyl-3-methylimidazolium chloride ([Emim][Cl]), 1-butyl- -3-methylimidazolium chloride ([Bmim][Cl]) and 1-hexyl-3-methylimidazolium chloride ([Hmim][Cl]), as extractive distillation entrainers, was also evaluated and compared to the conventional solvents, ethylene glycol and cyclohexane. Among the solvents studied, [Mim][Cl] required the lowest energy consumption, about 8% less energy use when compared to the optimized process using ethylene glycol. The multivariate statistical techniques employed were effective in the optimization of the extractive distillation processes as the process energy consumption could be minimized while achieving ethanol purity in agreement with the current specifications as well as obtaining a high solvent recovery. With the desirability approach it was possible to improve the process performance with little or no modification of existing processing plants.