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This article investigates the total PWM-induced power losses in interior permanent magnet (IPM) machines excited by wide bandgap (WBG)-based voltage-source inverters with different pulsewidth modulation (PWM) schemes and a wide range of switching frequencies. The PWM current ripple characteristics are predicted and compared using an accurate analytical model. Three enhanced power loss estimation models are utilized to estimate the PWM-induced power losses in each of three major machine materials: the stator form-wound windings, the stator and rotor iron cores, and the permanent magnets in the rotor cavities. The variation trend of each loss component versus PWM frequency and modulation scheme is provided. Experiments have validated the model accuracy in two IPM machines designed for traction applications. Both measured and predicted results suggest that increasing the PWM frequency is beneficial for suppressing the PWM-induced power losses in IPM machines. In conjunction with the reduction in machine-related power losses, it has also been demonstrated that a higher PWM frequency in IPM drives with WBG-based inverter exhibits the appealing potential for improving the system-level efficiency in traction applications. [ABSTRACT FROM AUTHOR]

This article presents an improved estimation model to predict the additional iron loss due to pulsewidth modulation (PWM) switching in interior permanent magnet (IPM) machines. The input current including the predicted PWM-induced current ripple is fed to two-dimensional (2-D) finite-element analysis to calculate the PWM-induced flux ripple distribution in the analyzed machine. A special frequency decomposition method is proposed to separate the predicted flux ripple into 1x and 2x PWM frequency components. Combining these results with the modified dynamic Jiles–Atherton model, the PWM-induced iron loss is calculated incorporating the impact of the actual flux ripple waveshape and the lamination steel's nonlinear magnetic characteristics. Experiments have been conducted to evaluate the prediction accuracy and investigate the impact of several factors on PWM-induced core losses (i.e., both iron and magnet loss) in IPM machines. These results demonstrate that the model offers promising estimation accuracy over a wide range of machine and inverter operating conditions. [ABSTRACT FROM AUTHOR]