Abstract
The solution of multiphysical problems in the field of electrical machines is a complex task that involves the modeling of a wide variety of coupled physical domains. Different types of models and solution methods can be used to model and solve the individual domains. In this paper a procedure for the methodical selection of the most suitable model for a given multiphysics task is presented. Furthermore, an approach for the selection of the most suitable variable machine parameters for a design optimization is presented. The model selection is presented on the basis of the electromagnetic calculation of an induction machine. For this purpose, models of different value ranges and levels of detail, such as analytical and numerical ones, are considered. The approach of the model selection is explained and applied on the basis of a coupled electromagnetic-thermal simulation of an exemplary induction machine. The results show that the model selection presented here can be used to methodically determine the most suitable model in terms of its value range, level of detail and computational effort for a given multiphysical problem.
Highlights
Calculation of Induction Machines.Complex tasks in the field of electrical machines usually comprise several physical domains and form a multiphysics problem
The permeance function is described as the product of the permeance functions of stator and rotor, which can be represented as infinite complex Fourier series due to the periodicity [4,11,12]. Accounting for these effects in combination with multiple armature reaction leads to a good approximation of the field behavior, which is illustrated in Figure 3 for the local variation of the air gap flux density Bδ compared to a linear T-Finite Element Method (FEM) simulation
Using the determined electromagnetic E-Harmonic Wave Model (HWM), the thermal behavior of the machine is simulated by means of the coupled simulation at the given operating point of 3700 rpm and 60 Nm
Summary
The individual models differ in their value range and level of detail of the representation of the physical effects as well as in their computational or solution effort They can be classified into the categories of empirical, analytical, lumped parameter, and numerical models. The proposed model selection approach can be used in machine optimization problems in which machines of similar power range but different designs are simulated to determine the appropriate models in individual optimization stages. Such an example is given in [3]. The parameter selection in combination with the model selection is applied in [3] in an optimization of the machine design of an IM
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
