Multi-Objective Optimization Design of the External Rotor Permanent Magnet-Assisted Synchronous Reluctance Motor Based on the Composite Algorithm

Based on the complex structural characteristics of permanent magnet-assisted synchronous reluctance motors (PMA-SynRMs), this paper proposes a multi-objective optimization design method for motor using composite algorithm. Firstly, power density, electromagnetic torque, cogging and torque fluctuation coefficient were used as targets based parametric analysis data 14 structure variables, where sensitivity helped select eight variables. Secondly, prediction model was fitted genetic algorithm–back propagation (GA-BP) neural network. Finally, non-dominated sorting algorithm-III (NSGA-III), reference points, to find complete external rotor PMA-SynRM with inputs four outputs. A comparative performance before after verifies feasibility optimizing This provides an analytical tool multi-parameter design.