Fast Iron Loss and Thermal Prediction Method for Power Density and Efficiency Improvement in Switched Reluctance Machines

To effectively find an optimal solution in the development process of electrical machines, it is essential to predict machine iron loss and thermal behavior in the predesign stage. Most existing publications only consider thermal behavior by roughly limiting the maximum current density. However, especially for high-speed application, iron loss can also be an essential part in thermal-behavior estimation. This paper proposes a simplified model to efficiently calculate iron loss and thermal behavior in the design procedure of switched reluctance machines. For this purpose, a maximum coenergy loop control method is implemented to facilitate the estimation of flux waveform and machine torque. Three different iron loss calculation methods are compared in terms of accuracy and time. Besides, a simplified lumped parameter thermal network is applied for machine sizing. Furthermore, the impact of number of turns and peak magnetomotive force on the losses and machine sizing is discussed. The efficiency and power density of various machine geometries are comparatively analyzed. Finally, the accuracy of the simplified model is verified by comparison with finite element simulations and experiment results.