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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]

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]

This paper presents an improved analytical model for estimating the high-frequency current ripple of interior permanent magnet synchronous machines due to pulsewidth modulation (PWM) switching. The proposed model accounts for the impact of slotting effect, magnetic saturation, and cross-coupling between the $d$ - and $q$ -axis. The model is subsequently used to investigate several factors that influence the PWM-induced current ripple. These include the PWM switching frequency, fundamental frequency (i.e., machine speed), dc-bus voltage, current control angle (i.e., γ angle), and the excitation current amplitude (i.e., saturation level). Experiments have been conducted to verify the analytical prediction results. These results show that the analytical model can predict the PWM-induced current ripple waveshape very well for many operating conditions and accurately estimate its rms value over a complete fundamental period. [ABSTRACT FROM AUTHOR]