Improved estimation of PC-SAFT equation of state parameters using a multi-objective variable-weight cost function

Abstract

Obtaining pure compound parameters and discerning among sets of parameter values that seem toperform equally well are major challenges when fitting equations of state (EoS) of the SAFT family. A newmethod to improve pure compound parameters estimation for SAFT EoS is proposed and applied to PC-SAFT. The method consists in using information from a sensitivity analysis to define an improvedvariable-weight cost function and fixing the least sensitive parameter. Using temperature dependentweights and fixing the least sensitive parameter, the model is fitted with a cost function skewed towardthe properties and temperature ranges where the EoS is more sensitive. To assess this approach, theperformance of parameters fitted with a classical unweighted cost function were compared with that ofparameters fitted with the new approach. Results from four 1-alkanols and four n-alkylamines show thatparameters fitted with the proposed methodology, when compared with those fitted with the classicalmethod, correlate non-associating parameters with molecular mass better. In addition, they fit andpredict mixture properties more accurately. Average binary VLE fitting error in liquid composition wasreduced from 7.2% to 6.5% and in vapour composition from 3.6% to 3.1%. In addition, mixture liquiddensity prediction error was reduced from 0.53% to 0.31%. Finally, ternary VLE average prediction errorwas reduced 15% for vapour compositions and 43% for temperature.