Prediction of EM Radiation from a PCB Driven by a Connected Feed Cable

Printed circuit boards (PCBs) driven by a connected feed cable are considered to be one of the main sources of the electromagnetic interference (EMI) from electronic devices. In this paper, a method for predicting the electromagnetic (EM) radiation from a PCB driven by a connected feed cable at up to gigahertz frequencies is proposed and demonstrated. The predictive model is based on the transmission line theory and current- and voltage-driven CM generation mechanisms with consideration of antenna impedance. Frequency responses of differential-mode (DM) and common-mode (CM) currents and far-electric field were investigated experimentally and with finite-difference time-domain (FDTD) modeling. First, the dominant component in total EM radiation from the PCB was identified by using the Source-Path-Antenna model. Although CM can dominate the total radiation at lower frequencies, DM is the dominant component above 3 GHz. Second, the method for predicting CM component at lower frequencies is proposed. And its validity was discussed by comparing FDTD calculated and measured results. Specifically, the relationship between the CM current and the terminating resistor was focused as important consequence for the prediction. Good agreement between the measured and predicted results shows the validity of the predicted results. The proposed model can predict CM current with sufficient accuracy, and also identify the primary coupling-mechanism of CM generation. Then far-electric field was predicted by using the proposed method, and it was demonstrated that outline of the frequency response of the undesired EM radiation from the PCB driven by the connected feed cable can be predicted with engineering accuracy (within 6 dB) up to 18 GHz. Finally, as example of application of equivalent circuit model to EMC design, effect of the width of the ground plane was predicted and discussed. The equivalent circuit model provides enough flexibility for different geometrical parameters and increases our ability to provide insights and design guidelines.