Optimal design of interior PM synchronous machines using randomly-guided mesh adaptive direct search algorithms

Newly proposed RG-MADS (Randomly Guided Mesh Adaptive Direct Search) has been applied to the optimal design of Interior Permanent Magnet Synchronous Motor (IPMSM) which has the distinctive features of magnetic saturation. RG-MADS, advanced from classical MADS algorithm, has the superiority in computational time and reliable convergence accuracy to the optimal solution, thus it is appropriate to the optimal design of IPMSM coupled with time-consuming Finite Element Analysis (FEA), necessary to the nonlinear magnetic application for better accuracy. Effectiveness of RG-MADS has been verified through the well-known benchmark-functions beforehand. In addition, the proposed RG-MADS has been applied to the optimal design of IPMSM aiming at maximizing the Maximum Torque Per Ampere (MTPA), which is regarded as representative design goal of IPMSM.