Advanced Soft- and Hard-Magnetic Material Models for the Numerical Simulation of Electrical Machines

Abstract

Accurate modeling of soft- and hard-magnetic materials for the numerical simulation of rotating electrical machines is required to allow predictions on the operational characteristics along the torque-speed map, already in the design stage. The full potential of most appropriate material selection and concurrent geometry adaption can only be utilized if models can represent actual material behavior. The accurate prediction of iron losses of soft-magnetic materials for various frequencies and magnetic flux densities, as well as the degradation due to manufacturing is eminent for the design of electrical machines. Therefore, advanced material models need to be adapted and their accuracy examined to further improve the modeling and enable progression. This paper will give an overview of the current modeling approaches applied at the Institute of Electrical Machines for soft- and hard-magnetic materials in the simulation of rotating electrical machines. A case example in the form of a traction drive is presented to which the models are applied. For the machine modeling, the inhouse solver pyMOOSE is utilized. In order to determine the losses with regard to manufacturing processes, the iron-loss model with material degradation is used in combination with a machine simulation scheme of the entire operating range of the machine. Here, various simulation approaches are combined to form the entire computational toolchain to obtain accurate results in the entire operational range.