Cost optimization of submersible motors using a genetic algorithm and a finite element method

This paper presents an optimal design method to optimize cost of three-phase submersible motors. The optimally designed motor is compared with an industrial motor having the same ratings. The motor design procedure consists of a system of non-linear equations, which imposes induction motor characteristics, motor performance, magnetic stresses, and thermal limits. The genetic algorithm (GA) is used for cost optimization, and a software algorithm has been developed. As a result of the realized optimization, besides the improvements on the motor cost, motor torque improvements have also been acquired. The 2-D finite element method (FEM) is then used to confirm the validity of the optimal design. Computer simulation results are given to show the effectiveness of the proposed design process that can achieve a good prediction of the motor performance. Through the studies accomplished, it has been observed that submersible induction motors' torques and efficiencies improve, their length reduces, and hence some material