Conducted electromagnetic interference analysis method for traction drive system in high speed trains

Yang, Zhichang; Li, Hong; Yang, Zhongping; Xu, Yue; Lin, Peng

doi:10.1109/itec-ap.2017.8080775

Cited by 3 publications

References 10 publications

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“…The overvoltage can result in accelerated aging or even failure of the motor winding insulation [3] . Moreover, the fast switching of semiconductors in the drive leads to conducted emissions [4][5] , such as the flow of the common-mode (CM) and differential-mode (DM) currents between the drive and motor [6][7] . These conducted emissions may disturb nearby sensitive equipment by various means, such as crosstalk [8] and common-ground interference [9] .…”

Section: Introductionmentioning

confidence: 99%

Physics Informed Neural Network-based High-frequency Modeling of Induction Motors

Zhao

Fan

Jie

et al. 2022

Chin. J. Electr. Eng.

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The high-frequency (HF) modeling of induction motors plays a key role in predicting the motor terminal overvoltage and conducted emissions in a motor drive system. In this study, a physics informed neural network-based HF modeling method, which has the merits of high accuracy, good versatility, and simple parameterization, is proposed. The proposed model of the induction motor consists of a three-phase equivalent circuit with eighteen circuit elements per phase to ensure model accuracy. The per phase circuit structure is symmetric concerning its phase-start and phase-end points. This symmetry enables the proposed model to be applicable for both star-and delta-connected induction motors without having to recalculate the circuit element values when changing the motor connection from star to delta and vice versa. Motor physics knowledge, namely per-phase impedances, are used in the artificial neural network to obtain the values of the circuit elements. The parameterization can be easily implemented within a few minutes using a common personal computer (PC). Case studies verify the effectiveness of the proposed HF modeling method.

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