A Switched Reluctance Motor (SRM) can be optimized on two fronts; the magnet design itself and the dynamic performance.
Such a motor can be easily simulated with parametric magnetostatic solutions using either the CST EM STUDIO® (CST EMS) 2D or 3D magnetostatic solvers. Only a single 3D model is required for both types of simulation ensuring that the geometry, excitation, materials and boundary conditions are consistent between the 2D and 3D models. The user merely has to specify the cut-plane in the 3D model on which the 2D simulation should be performed. Full parametric and post-processing capabilities are defined independent of the solver choice. This allows the user to, for example, perform rapid 2D parametric analyses and obtain end-effect correction factors from a 3D simulation for the same model. ...
An example of a 6/4 SRM is shown in figure 1 which was rapidly constructed in CST EMS. Non-linear materials have been defined for both the stator and rotor components. Although three coil pairs have been defined, only one pair needs to be excited for the simulations due to the symmetric properties of the motor.
Figure 2 shows the flux lines, vector potential, for the unaligned rotor position from the 2D solution.
Such a reluctance machine is controlled by, for example, an asymmetric bridge converter. For a dynamic simulation, it is important to extract specific quantities from the parametric data in look-up table form. Torque, flux-linkage and co-energy amongst other data can be automatically exported as functions of angular displacement, current and other user-defined parameters.
The results from a parametric sweep of flux linkage as a function of current and angular displacement are shown in Figure 3. The aligned position corresponds to zero degrees.
The results from a parametric sweep of torque as a function of current and angular displacement are shown in Figure 4. Again, the aligned position corresponds to zero degrees.
In addition to the parametric analysis, optimization of the magnetic performance of the motor can be performed using the built-in optimizer. Parameters such as the stator and rotor pole widths can be optimized to reduce the peak flux density and increase the mechanical stiffness. Tapering of the pole edges can be applied to the model, the level of which can be optimized to reduce the harmonics in the torque waveforms.