Min-Max Univariate Dynamic Encoding Algorithm for Searches (uDEAS) and Its Application to Optimal Design of Electric Machines

Optimal design of Interior Permanent Magnet Synchronous Machines (IPMSM) is to obtain the global design optimum in association with the characteristic analysis investigating nonlinear magnetic saturation based on Finite Element Analysis (FEA). Since characteristic analysis occupies most part of the convergence time, the number of objective function must be called minimally. Hence, in this paper, MuDEAS is newly implemented in order to compensate the excessive computation time and the reliability of convergence to the global optimum. MuDEAS has been verified through a benchmark function and applied to the optimal design of IPMSM for maximizing Maximum Torque Per Ampere (MTPA) indentified with FEA.