Optimal Design of a Permanent Magnet Synchronous Motor Using the Cultural Algorithm In this project, a permanent magnet synchronous motor (PMSM) structure is optimized by a single-objective optimization method known as the cultural algorithm (CA). The torque capability of the PMSM is high due to the presence of permanent magnets (PMs) in its structure. However, in critical applications with limited space (especially with volume limitation), the torque density is a more prominent function than the torque. For this reason, in the optimization problem presented in this paper, the torque density is the objective function. Therefore, this study aims to maximize the torque capability at a specified space besides maintaining the torque ripple under a specified value (as a constraint). To this, the structural parameters of the machine are optimized by the CA. The results of the optimization process would be presented and compared with the initial machine design. These results demonstrate that the CA increases the torque density of the machine and keeps the torque ripple under the specified value.
Permanent magnet synchronous motors are a popular option for electric vehicles. The structure of the motor should be optimized to push the limits of the efficiency of the whole drive to the maximum point. So, the single and multi-objective optimization techniques were implemented on the mo- tor structure for performance improvement. Various expectations are available in the field of motor optimization. Torque and cost performances are the most required criterion in most applications. For torque performance, usually, the average torque, torque ripple, and cogging torque are \considered. Similarly, the cost performance can be estimated from the initial cost and power losses of the motor during operation. So, in most industrial projects and research studies, designers attempt to improve them using optimization algorithms. It is essential to mention that there is a vast category for optimization algorithms, and if we want to choose between them, we might confuse them a little.
A reliable optimization algorithm for engineering applications should have some specifications such as high convergence speed, robustness, and
large-scale capability. Considering all these criteria, we can reliably use the metaheuristic optimization algorithms as they could provide the
best solutions for benchmark problems and several engineering problems [1-5].
In this project, the cultural algorithm from the family of evolutionary-based algorithms has been implemented on the structure of a surface-
mounted permanent magnet synchronous motor to bring up substantiate features of torque capability and low cost.
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