Multi-objective Optimal Design of a Five-Phase Fault-Tolerant Axial Flux PM Motor

Abstract

Electric motors used for traction purposes in electric vehicles (EVs) must meet several requirements, including high efficiency, high power density and fault-tolerance. Among them, permanent magnet synchronous motors (PMSMs) highlight. Especially, five-phase axial flux permanent magnet (AFPM) synchronous motors are particularly suitable for in-wheel applications with enhanced fault-tolerant capabilities. This paper is devoted to optimally design an AFPM for in-wheel applications. The main geometric, electric and mechanical parameters of the designed AFPM are calculated by applying an iterative method based on a set of analytical equations, which is assisted by means of a reduced number of three-dimensional finite element method (3D-FEM) simulations to limit the computational burden. To optimally design the AFPM, a constrained multi-objective optimization process based on a genetic algorithm is applied, in which two objective functions are considered, i.e. the power density and the efficiency. Several fault-tolerance constraints are settled during the optimization process to ensure enhanced fault-tolerance in the resulting motor design. The accuracy of the best solution attained is validated by means of 3D-FEM simulations.

Keywords

• motor design
• fault-tolerance
• optimization
• permanent magnet machines
• sizing equations