Multi-Objective Optimal Design of Surface-Mounted Permanent Magnet Motor Using NSGA-II - Mendaci, S.; Allag, H.; Mekideche, M. R. (Applied Computational Electromagnetics Society Journal (ACES), 2021)
This paper presents a highly structured procedure for multi-objective optimal design of radial surface Permanent-Magnet Synchronous Motor (PMSM). Firstly, a detailed analytical model based on the resolution of Maxwell’s equations using the separation of variables method is presented. From the same model, analytical expressions of four constraint functions dedicated for the optimal design of the PMSM are developed. These constraints are: electromagnetic torque, back electromotive force (back-EMF), flux density saturation in stator/rotor yoke and saturation in stator tooth. Then, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is employed to optimize the multi-objective problem formed by two objective functions (weight and power loss of the motor) and different constraints. Finally, the finite element method is used to validate the designed 30 kW PMSM.