Exergy efficiency can be used as an objective function in order to improve systems efficiency. Thus, the most efficient regions for the operation parameters can be searched easily. Exergy efficiency data of a turboprop engine’s components that have been calculated using basic engine parameters in the previous studies are modeled using cubic spline curve fitting methodology. Spline curves are on the two dimensional plane, where x axis is the input parameter and y axis is the exergy efficiency of the component. A spline curve is defined by the points subject to arbitrary selection of number and position. Initially positions of the points are located with two different methods and then in order to obtain better accuracy point positions are improved by ‘Ant colony’ and ‘Goldsection’ optimisation methods. Sum of Squares of the errors between the fitted value and data value was used as the fitness function. Least square error of 5 × 10−9 is assumed as acceptable accuracy which yields to a minimum R = 0.9998 linear correlation coefficient. In the optimisation step, independent engine variable versus calculated engine performance parameters were checked against spline fitted values. Improvement of the fitness function is observed as the number of fitting points is increased. Ant colony optimisation in engine exergy efficiency parametric modeling is a new approach in authors’ point of view.
