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This study presents a time-efficient modelling approach for dynamic behavior and efficiency analysis of a Switched Reluctance Machines (SRM). It employs a hybrid model combining Simulink, finite element analysis (FEA), and hardware measurements to create an accurate behavioral model of the machine. In order to enhance accuracy of the estimated performance, Steinmetz equation is employed to characterize core loss in the machine across different operating points. This approach serves as a template for developing a time-efficient model to analyze performance of any SRM with a high degree of accuracy. Simulation and experimental results are used to show effectiveness of the proposed approach. 

This study presents a computationally cost-effective modeling approach for a switched reluctance machine (SRM) towards predicting vibration and acoustic noise. In the proposed approach, the SRM is modeled using Finite Element (FE) software for capturing magnetic snapshots from static simulations. Using an advanced field reconstruction method (FRM), these snapshots are used to develop basis functions to estimate magnetic fields under any arbitrary stator excitation and at any desired rotor position. This method includes magnetic properties of the machine and can estimate flux density at once instead of partially predicting it. The vibration model is built in FE software while the acoustic noise is predicted using the analytical method. The proposed study can significantly reduce the computational time for vibration and noise analysis with decent accuracy. Dynamic simulation by finite-element analysis (FEA) software and experimental verification have been carried out to verify the effectiveness of the proposed hybrid model. 

This paper presents a comparative evaluation of power electronic control approaches for vibro-acoustic noise reduction in High Rotor-Pole Switched Reluctance Machines (HR-SRM). It carries out a fundamental analysis of approaches that can be used to target acoustic noise and vibration reduction. Based on the comprehensive study, four candidates for control have been identified and applied to the HR-SRM drive to evaluate their effectiveness and identify challenges. These four methods include phase advancing, current shaping based on field reconstruction, and random hysteresis band with and without spectrum shaping. The theoretical background, implementation, and vibro-acoustic noise reduction performance of each method are presented in detail. Comparative studies from simulation and experimental measurements have been used to identify the most effective solution to acoustic noise and vibration reduction in HR-SRM configuration.