Accurate Noise Source Separation in Pulse-Frequency Modulation-Controlled Power Converters Using Asynchronous Near-Field and Far-Field Measurement Analysis

Aperiodic spike noise signals generated by pulse-frequency modulation (PFM)-controlled direct-current (DC)–DC converters introduce random jitter into the switching timing, rendering it challenging to isolate individual power supply noise sources. Conventional methods based on cross-correlation analysis suffer from inaccuracies owing to the random jitter and aperiodic characteristics inherent in PFM converters. This study proposes a method for accurately separating radiated electromagnetic noise sources from multiple PFM-controlled DC–DC converters. An asynchronous near-field and far-field measurement scheme is adopted owing to its considerably lower implementation cost than that of its synchronous counterpart. The proposed method extracts individual spike noise, and then identifies and associates each with its corresponding source based on the spatial and temporal characteristics captured by the asynchronous measurements. The experimental results demonstrate improved estimation accuracy across a broad bandwidth, thereby enabling the identification of dominant noise sources. This enhanced accuracy supports more efficient mitigation of electromagnetic interference and reduces the complexity and cost of implementing noise suppression. As a result, the time-to-market can be shortened, facilitating the development of cost-effective electronic products.

Authors

Institutions

Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3610518
Primary Topic
Electromagnetic Compatibility and Measurements
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Accurate Noise Source Separation in Pulse-Frequency Modulation-Controlled Power Converters Using Asynchronous Near-Field and Far-Field Measurement Analysis

Hidekatsu Sasaki, Kenta Umebayashi, Yasuaki Kaneda, Satoshi O. Suzuki et al.
IEEE Access
Electromagnetic Compatibility and Measurements
article

Accurate Noise Source Separation in Pulse-Frequency Modulation-Controlled Power Converters Using Asynchronous Near-Field and Far-Field Measurement Analysis

Hidekatsu Sasaki, Kenta Umebayashi, Yasuaki Kaneda, Satoshi O. Suzuki, Hiroyasu Sano
article en

Abstract

Aperiodic spike noise signals generated by pulse-frequency modulation (PFM)-controlled direct-current (DC)–DC converters introduce random jitter into the switching timing, rendering it challenging to isolate individual power supply noise sources. Conventional methods based on cross-correlation analysis suffer from inaccuracies owing to the random jitter and aperiodic characteristics inherent in PFM converters. This study proposes a method for accurately separating radiated electromagnetic noise sources from multiple PFM-controlled DC–DC converters. An asynchronous near-field and far-field measurement scheme is adopted owing to its considerably lower implementation cost than that of its synchronous counterpart. The proposed method extracts individual spike noise, and then identifies and associates each with its corresponding source based on the spatial and temporal characteristics captured by the asynchronous measurements. The experimental results demonstrate improved estimation accuracy across a broad bandwidth, thereby enabling the identification of dominant noise sources. This enhanced accuracy supports more efficient mitigation of electromagnetic interference and reduces the complexity and cost of implementing noise suppression. As a result, the time-to-market can be shortened, facilitating the development of cost-effective electronic products.

IEEE AccessVol. 13
Tokyo Metropolitan Industrial Technology Research Institute (JP), Tokyo University of Agriculture and Technology (JP)
Openalex Percentile: Top 76%
Electromagnetic Compatibility and Measurements
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.