Conducted Noise Prediction for DC–DC Converter by Noise Source Model Accounting for Switching Fluctuation

The switching fluctuation of a dc–dc converter causes jitter and makes the conducted noise time-variant. Averaging-mode measurement with an oscilloscope or other instruments partially removes higher-frequency noise. Therefore, switching fluctuation affects the accuracy of noise prediction in using a black-box noise source model with measurement-based parameter identification. To address this issue, we proposed an approach to address the switching fluctuation effect on conducted emissions from the dc–dc converter. First, we investigate the effect of switching fluctuation by studying the difference between noise signals with and without fluctuation and estimating the reduction due to fluctuation. Then, to facilitate model parameter identification, we focus on the peak detected noise signal and improve the prediction accuracy of the peak detected noise by decomposing the measured noise signal into ripple noise and turn-
on
and turn-
off
spike noises. As a result, the peak detected noise spectrum after removing switching fluctuation can be predicted within a 3-dB error up to 200 MHz. Our experimental results show that the noise spectrum predicted by accounting for the reduction due to switching fluctuation agrees well with the spectrum obtained by averaging-mode measurement.