Modified Mutation based Rao-3 Algorithm for Design Optimization of Surface Inset PMSM via Multi-Echelon Strategy

The problem of design optimization of Surface Inset type of Permanent Magnet Synchronous Motor, or SI-PMSM, requires the consideration of large number of its design parameters. It arises the issue of making the decision about the design parameters, such as, what parameters should be optimized and what parameters can be left out. Due to this, the high computation time and cost is fostered. To address this problem, this paper presents a novel multi-echelon strategy (MES) based design optimization framework by introducing a new modified mutation based Rao-3 algorithm (MMRA) for the minimization of overall losses in the motor. For dividing various design parameters into three echelons, the proposed MES-MMRA technique employs Kendall correlation coefficient nalysis. The MES technique helps to separate significant and non-significant design parameters by analyzing the corresponding z-scores of all parameters statistically. It is shown that the newly introduced MMRA technique performs much better than other modern meta-heuristic algorithms. The proposed MES-MMRA technique has been able to perform well in solving the design optimization problem of SI-PMSM. As a result, the minimum loss obtained, by applying MMRA algorithm to the loss problem, is 136.215 W, leading to a saving of 29% of the loss obtained from un-optimized initial model. Through this paper, the proposed mechanism can also efficiently improve the motor’s overall electromagnetic performance. This results in the increase in the efficiency of the motor by 2.7 %. The technique of Finite Element Analysis, or FEA, is carried out to validate and verify the results.