The fan design optimization for totally enclosed type induction motor with experimentally verified CFD-based MOGA simulations

Abstract

The energy efficient electric motors save energy thus reduce operating costs. Since there are several losses affecting the motor efficiency, fan design plays an important role to minimize these losses. This study examines the effects of the design parameters of a radial bladed fan on the motor efficiency in a 132 frame with a power of 7.5 kW. The parametric analysis was carried out with the computational fluid dynamics method, and the results were used for the multiobjective genetic algorithm (MOGA) optimization study with the highest efficiency and the lowest motor body temperature objectives. The hub height, hub radius, distance to body cover, blade rising angle, fan cover entrance distance, blade edge angle, blade center radius, blade edge radius, blade end radius, and center edge distance were selected as optimization parameters. 151 simulations were performed. The results showed that the most important parameter for fan efficiency is the hub height which is the parameter that determines the height of the fan impeller diameter. According to the results, the optimum fan design increased the efficiency by 8% compared to the original fan and reduced the winding temperature by 8 °C. The optimized fan design was manufactured and tested against imulation data. This study contributes to sustainable development goals by improving motor efficiency that reduces the cost, designing of new components, and cooling the fan effectively that reduces the amount of copper used.