Optimization Design of Electrical Axial Fan Based on NSGA - II Algorithm

A fast sequencing genetic algorithm, NSGA-II is applied to the performance optimization of axial flow electric fans on multi eletric aircraft to improve the effectiveness of environmental control systems (ECS) and reduce fuel penalty. The degree of sweep and curve of blades is set as the optimization parameters, while low power and large flow rate is set as the optimization objectives to optimize the initial design. NSGA-II algorithm is used to control the optimization parameters, and an automated simulation analysis process is established to achieve automatic iteration and optimization. The power of the optimized fan model is reduced by 8.8% compared to the prototype. The results show that the method used in this paper has good effects in dealing with multi-objective and multi-parameter performance optimization problems of axial flow fans. The method has also certain reference value for the optimization design of other turbomachine.