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Optimum pole combination to maxmize torque density in switched reluctance motors for electric vehicle applications

Tarvirdilu Asl, Rasul
Nowadays, using Switched Reluctance Motors (SRM) as a substitute for Interior Permanent Magnet Synchronous Motors (IPMSMs) in hybrid electric vehicle applications is of great interest. The main advantage of using SRM is elimination of permanent magnet materials in machine structure. In addition, simple and robust structure, high rotational speeds and operation at higher temperatures are other benefits of using switched reluctance motors. In this study, a combined analytical and Finite Element (FE) based method is implemented which has both the rapidity of analytical computations and the accuracy of finite element method. Normalized permeance, force and MMF data are obtained using a finite element based software for a symmetrically slotted geometry. Data sets are produced for different normalized teeth widths, normalized air gap lengths, normalized rotor positions and MMF values. The produced data are used as a look up table in calculation of normalized permeance, force and flux density values in tooth-air gap region of switched reluctance motors. It is worth mentioning that all nonlinearities and saturation effects are taken into account while using this method. The proposed method is capable of calculating static and dynamic performance characteristics of switched reluctance motors with an acceptable range of accuracy. Furthermore, an analytical model based on actual variation of core flux and its harmonic components is developed to calculate core loss and efficiency of the SRM. In order to corroborate the precision of the proposed analytical model, two switched reluctance motors are simulated using 2D finite element method. Comparing analytical calculations with simulation results and measurements proves the accuracy of the model and its suitability to be used for optimization purposes. A general design methodology is proposed which can be used in designing switched reluctance motors to be used in various applications. At the final step, Genetic Algorithm (GA) optimization method is implemented to determine the optimum pole combination, geometry and excitation pattern for a 50 kW switched reluctance motor to be used in a specific hybrid electric vehicle application. Designing a high torque density switched reluctance motor is the main aim of the optimization problem. Finally, the optimized SRM is simulated using finite element method to validate optimization results. Improvements in torque density and efficiency of the machine is compared to existing prototypes in the literature for this specific application.