TY - GEN
T1 - An Approach to Predicting Conducted Noise from DC-DC Converter Accounting for Switching Fluctuation
AU - Zhang, Shuqi
AU - Iokibe, Kengo
AU - Toyota, Yoshitaka
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Switching fluctuation, which causes jitter, occurs in a DC/DC converter's clock signal, which causes conducted noise to be time variant. An oscilloscope's averaging mode in the measurement partially removes high-frequency noise. Thus, the accuracy when predicting the noise by model identification based on the black-box equivalent circuit model is affected by switching fluctuation. In this paper, we first focus on removing the effect of switching fluctuation and improving the accuracy of noise prediction by using the noise signal decomposition method. We propose a method for decomposing a measured time-domain noise signal into ripple noise and turn-on and turnoff spike noises to prevent the accuracy from degrading in parameter identification. The waveform decomposition method for peak detection can be used to predict the noise spectra without switching fluctuation within a 3-dB prediction error for up to 200 MHz. In reality, switching fluctuation spreads the power density of the measured signal. Thus, our second area of focus is predicting the reduced noise spectrum when switching fluctuation occurs. The noise level of the predicted spectrum agrees well with that of the measured one.
AB - Switching fluctuation, which causes jitter, occurs in a DC/DC converter's clock signal, which causes conducted noise to be time variant. An oscilloscope's averaging mode in the measurement partially removes high-frequency noise. Thus, the accuracy when predicting the noise by model identification based on the black-box equivalent circuit model is affected by switching fluctuation. In this paper, we first focus on removing the effect of switching fluctuation and improving the accuracy of noise prediction by using the noise signal decomposition method. We propose a method for decomposing a measured time-domain noise signal into ripple noise and turn-on and turnoff spike noises to prevent the accuracy from degrading in parameter identification. The waveform decomposition method for peak detection can be used to predict the noise spectra without switching fluctuation within a 3-dB prediction error for up to 200 MHz. In reality, switching fluctuation spreads the power density of the measured signal. Thus, our second area of focus is predicting the reduced noise spectrum when switching fluctuation occurs. The noise level of the predicted spectrum agrees well with that of the measured one.
KW - conducted emissions
KW - equivalent noise-source model
KW - spread-spectrum clocking
KW - switching fluctuation
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U2 - 10.1109/APEMC49932.2021.9596844
DO - 10.1109/APEMC49932.2021.9596844
M3 - Conference contribution
AN - SCOPUS:85123411431
T3 - Proceedings of the 2021 Asia-Pacific International Symposium on Electromagnetic Compatibility, APEMC 2021
BT - Proceedings of the 2021 Asia-Pacific International Symposium on Electromagnetic Compatibility, APEMC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 Asia-Pacific International Symposium on Electromagnetic Compatibility, APEMC 2021
Y2 - 27 September 2021 through 30 September 2021
ER -