High‐frequency modelling of permanent magnet synchronous motor for conducted EMI studies

Abstract

In this work, a high‐frequency model of permanent magnet synchronous motor (PMSM) is proposed for using in conducted electromagnetic interference (EMI) modelling and simulation of variable speed drive systems. The presented model covers the defined frequency range for the conducted emissions, based on MIL‐STD‐461 and FCC/CISPR standards from 10 kHz to 30 MHz. Common‐mode (CM) and differential‐mode (DM) impedance characteristics of PMSM are measured; the proposed method is based on the behavioural method using the measurement data. However, in order to improve the mid‐frequency representation, the model is enhanced by physics‐based methods with parameters extracted directly from the physical properties of the motor using a three‐dimensional finite element method and analytical calculations. This approach enables us to avoid the trial and error method and fine‐tuning the model parameters. In order to validate the calculated CM and DM impedances of the PMSM, simulation results are compared with the experimental measurements. Root mean squared relative error is introduced to measure the accuracy of the proposed model and also to compare the given results with the models previously presented in the literature.

Overview of Sensorless Zero-Low Speed Range Control Technology based on High-Frequency Signal Injection for SPMSM

“…and the injected voltage amplitude is consistent with the change of PWM period, as shown in figure 6b. Combined with PMSM high-frequency mathematical model [15][16], the high-frequency response current in ˆdq  coordinate system can be rewritten as follows:…”

EMC Component Modeling and System-Level Simulations of Power Converters: AC Motor Drives

“…The circuit parameters can then be extracted from the measurements using either pre-defined equivalent circuit topologies that emulate the physical behavior of the motors [29,93,95,102,121,[127][128][129][130][131][132][133][134] or more general circuit topologies based on rational function approximations [135,136] and vector fitting algorithm [17,19,137,138]. A combination of FEM and behavioral modeling may also be used to improve and fine-tune the model parameters [139].…”