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The availability of wide-bandgap (WBG) power switches makes it possible to excite electric machines with much higher pulsewidth modulation (PWM) switching frequencies. This article experimentally characterizes the magnetic and iron loss properties of lamination steels over a wide range of PWM frequencies and magnetization states excited by a voltage-source inverter using GaN-based WBG switches. With the collected hysteresis loop and iron loss data, a new frequency-interconnected dynamic Jiles–Atherton (J–A) model has been developed explicitly for PWM-induced iron loss analysis. Experiments have been conducted to verify the model prediction accuracy over a broad range of operating conditions. The proposed model has been subsequently integrated with a dynamic hysteresis model devoted to fundamental field iron loss estimation, providing an accurate and efficient tool for total iron loss estimation during PWM voltage excitation using high-frequency WBG devices. This article includes an investigation of the impact of elevated fundamental frequencies and field amplitudes on the total iron loss including comparisons between analytical predictions and experimental test results. [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]

This article investigates the iron loss properties of soft magnetic materials under conditions of high excitation frequency and varying premagnetized dc-bias fields (i.e., different magnetization states). Using measured iron loss data collected from the customized test equipment, a modified dynamic Jiles–Atherton model has been developed specifically for the purpose of achieving improved pulsewidth modulation (PWM)-induced iron loss estimation. The accuracy and scalability of the proposed prediction model for different conditions are evaluated including the flux ripple amplitude, excitation frequency, dc-bias field, and symmetry of the triangular waveform. Experimental results have confirmed that the proposed model can accurately predict the dynamic hysteresis loop and corresponding iron loss over a wide range of operating conditions. By introducing a companion iron loss model developed for fundamental and low-order harmonic fields, the total iron loss under inverter PWM voltage excitation is explored. The results show that model parameters derived from a limited number of tests can be used to predict the iron loss in a much broader operating range, which makes it a promising tool for PWM-induced iron loss estimation in new machine designs intended for demanding operating conditions. [ABSTRACT FROM AUTHOR]