Optimizations of turboprop engines using the non-dominated sorting genetic algorithm

摘要

This article presents a Pareto approach to design for the optimal performance of four configurations of turboprop engines matching the power requirements of a class of propeller-driven aircrafts. In these bi-objective optimizations of the thermal cycle parameters, the power-specific fuel consumption is minimized and the specific power is maximized while maintaining the power levels and limiting the temperature of the power turbine blades. For this purpose, a multi-objective evolutionary optimization algorithm called non-dominated sorting genetic algorithm is used. To avoid engine performance deterioration and constraint violation at extreme operating conditions, the objective functions and constraints are evaluated at both design and off-design conditions. The trade-off surfaces representing the sets of alternative solutions are obtained based on the Pareto optimality. By considering additional subjective criteria, three design points are proposed for each engine configuration.