A New Multi-Modal Optimization Approach and Its Application to the Design of Electric Machines

Abstract

The latest electric machine design procedure is a complex non-linear multi-constrained optimization problem that takes a considerable amount of time to calculate and analyze electromagnetic fields. To address this issue adequately, this paper proposes a new metaheuristic multi-modal optimization design procedure based on the modified water cycle algorithm and supported by a surrogate model using the compressed sensing method. The proposed approach explores multiple optimal solutions simultaneously with good computational efficiency by reducing the number of cost function calls used in the optimization process. The efficiency of the proposed method is investigated by applying it to a set of test functions. Furthermore, the validity of the proposed approach with respect to the application to an electromagnetic problem is verified by designing a brushless permanent magnet tachogenerator using it.