A Modified Genetic Algorithm for the Selection of Decoupling Capacitors in PDN Design
Abstract
Decoupling capacitors are used to provide adequate and stable power for integrated circuits in printed circuit boards (PCB). For complicated and large designs, it is difficult to select capacitors to meet voltage ripple limits while also minimizing cost because the search space is too large. In this work, a new genetic algorithm (GA) is proposed for the selection and placement of capacitors to meet a target impedance using as few capacitors as possible. The GA is centered around controlling the number of unused port locations in the GA population solutions, with the result of smoothing out the GA convergence and speeding up the convergence rate. A result comparison is made of the proposed GA against other algorithms and found the GA competitive if not better for the select test cases.
Recommended Citation
J. Juang et al., "A Modified Genetic Algorithm for the Selection of Decoupling Capacitors in PDN Design," Proceedings of the 2021 Joint IEEE International Symposium on EMC/SI/PI, and EMC Europe (2021, Raleigh, NC), pp. 712 - 717, Institute of Electrical and Electronics Engineers (IEEE), Aug 2021.
The definitive version is available at https://doi.org/10.1109/EMC/SI/PI/EMCEurope52599.2021.9559292
Meeting Name
2021 IEEE International Joint Electromagnetic Compatibility Signal and Power Integrity and EMC Europe Symposium, EMC/SI/PI/EMC Europe 2021 (2021: Jul. 26-Aug. 13, Raleigh, NC)
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Electromagnetic Compatibility (EMC) Laboratory
Keywords and Phrases
Decoupling Capacitor; Genetic Algorithm; Power Distribution Network; Printed Circuit Board
International Standard Book Number (ISBN)
978-166544888-8
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2021 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
13 Aug 2021
Comments
This work was supported in part by the National Science Foundation (NSF) under Grant IIP-1916535.