Evolved Motor Design Process to Reduce the Design Expense of Axial Flux Permanent Magnet Motor

This paper proposes a design process that combines an initial electromagnetic design using analytical techniques with an optimal design based on a multi-objective optimization algorithm, aiming to reduce the design cost of an axial flux permanent magnet motor for urban air mobility traction. In the initial design step, key parameters are determined using an analytical method, followed by a detailed design that accounts for magnetic saturation. Design variables with significant impact on performance are selected, and an optimal design is conducted using a multi-objective optimization algorithm. The analytical method employs the space harmonic method to calculate the motor’s magnetic field distribution using Fourier series, while the conformal mapping method considers the slot effect by incorporating it into the air gap flux density. The Quasi-3D method approximates 3D analysis with multiple 2D analyses, enabling rapid evaluation of various models. The optimization algorithm reduces computational time by constructing a meta-model using a kriging function, which enables direct addition of solutions within the objective function area, thereby avoiding repeated evaluations of the actual objective function. Finally, a prototype motor was fabricated and tested to validate the proposed process. The experimental results showed strong agreement with the simulation outcomes, confirming the accuracy and applicability of the proposed design approach.