We developed a high-efficiency half-ducted propeller fan to reduce the electric power consumption of the outdoor unit of a packaged air conditioner by using a design tool combining computational fluid dynamics (CFD) with multi-objective optimization techniques based on a genetic algorithm (GA). The baseline fan was a half-ducted propeller fan with three blades of a currently available product. Blade shape was defined using 16 design variables including inlet and outlet blade angles, setting angles, blade length, sweep angles, dihedral angles, and so on. An in-house program was used to automatically generate the grids for CFD calculation. The objective functions were static pressure efficiency and fan noise level for optimization. The fan noise was calculated with an aerodynamic noise prediction model that used the relative inlet and outlet velocities of the fan blades from the CFD results. We found there was a trade-off relationship between the static pressure efficiency and the fan noise. We then selected the optimized fan that had the same noise level as the baseline fan but with an improved static pressure efficiency. The blade tip of the optimized fan was curled toward the suction side direction. Finally, we confirmed through experiments that the static pressure efficiency of the optimized fan was increased by 1.6% compared to the baseline fan.

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