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 to perform equally well are major challenges when fitting equations of state (EoS) of the SAFT family. A new method 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 improved variable-weight cost function and fixing the least sensitive parameter. Using temperature dependent weights and fixing the least sensitive parameter, the model is fitted with a cost function skewed toward the properties and temperature ranges where the EoS is more sensitive. To assess this approach, the performance of parameters fitted with a classical unweighted cost function were compared with that of parameters fitted with the new approach. Results from four 1-alkanols and four n-alkylamines show that parameters fitted with the proposed methodology, when compared with those fitted with the classical method, correlate non-associating parameters with molecular mass better. In addition, they fit and predict mixture properties more accurately. Average binary VLE fitting error in liquid composition was reduced from 7.2% to 6.5% and in vapour composition from 3.6% to 3.1%. In addition, mixture liquid density prediction error was reduced from 0.53% to 0.31%. Finally, ternary VLE average prediction error was reduced 15% for vapour compositions and 43% for temperature.