Cogging torque is an important issue in design of permanent magnet motors, especially in certain high accuracy applications. Most of the methods utilized for cogging torque reduction lead to motor structure complexity, increasing manufacturing cost and also influencing the output torque. This research tries to find an optimal solution set of the PMSM with the aim of reducing the cogging torque while the output torque is not affected. For this purpose, multi-objective optimization is a proper and reliable approach which can provide the solution set involving conflicting functions simultaneously. Multi-objective optimization determines the logical range of cogging torque reduction with respect to the output torque. In this paper, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which is a powerful and well-known multi-objective optimization method, is applied to find the optimal design of a surface-mounted Permanent Magnet Synchronous Motor (PMSM). Simulation results show efficacy of the NSGA-II. In the suggested design solutions that are selected from the Pareto-optimal set, cogging torque is reduced considerably while the output torque has experienced a slight decrease with respect to the nominal value. At last, time-stepping Finite-element Analysis (FEA) is used to validate the multi-objective optimization.
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