A novel forward computational modal analysis method of the motor stator assembly considering core lamination and winding stacking

The forward computational modal analysis (CMA) of the motor stator assembly is gaining attention as a technical challenge in the area of motor noise. There is still no effective method to obtain accurate anisotropic material parameters (AMPs) required for CMA without prototype motors. In this paper, a novel forward calculation method (FCM) for calculating AMPs of the motor stator assembly is proposed, in considering structural discontinuities and composite material properties due to core lamination and winding stacking. The method is based on multi-scale theory. Firstly, the multi-scale equations coupling the macroscopic model and the mesoscopic model of the stator core and winding are established. By decoupling the multi-scale equations, the equivalence and equivalence preconditions of AMPs of the two scale models are described. Accordingly, the finite element method (FEM) for calculating AMPs of the stator core and winding based on the mesoscopic model is proposed. Then, the AMPs of the stator core and winding are calculated by the FCM, and the influencing factors are further studied, respectively. Finally, the effectiveness of this method is verified by modal experiments. Compared with experimental results, the maximum relative error of natural frequencies of the stator assembly is within 1.5%. This method can achieve accurate CMA without prototype motors and modal experiments, which contributes to the accurate prediction and control of electromagnetic noise in the initial motor design stage.

Automated summary

This paper proposes a novel forward calculation method (FCM) for calculating anisotropic material parameters (AMPs) of the motor stator assembly, considering structural discontinuities and composite material properties. The method is based on multi-scale theory and decouples the multi-scale equations to describe the equivalence and equivalence preconditions of AMPs of two scale models. The effectiveness of this method is verified by modal experiments.