A Pattern-Based Analytical Method for Impedance Calculation of the Power Distribution Network in Mobile Platforms
A power distribution network (PDN) is essential in electronic systems to provide reliable power for load devices. With faster load transient current and lower voltage tolerance margin for microprocessors in mobile platforms, it is crucial to optimize the printed circuit board (PCB) design to satisfy the strict target impedance. Conventional modeling methods become impractical in mobile platforms due to the characteristics of high-density interconnect PCB and limited layout space. To overcome these issues, a pattern-based analytical method for the PDN impedance calculation is presented in this article. Based on the localized patterns formulated by the relative relationships between the adjacent vias, parasitic elements are analytically determined for different regions of the entire PCB structure. With the assistance of this method, a practical modeling methodology is developed to construct an equivalent circuit with one-to-one correspondence to the PCB's physical geometry. As a result, the PDN design can be efficiently optimized, especially in the predesign stage, to accelerate the development process. Finally, the proposed method is validated by measurements and full-wave simulations using a real mobile phone PCB in production.
J. Sun et al., "A Pattern-Based Analytical Method for Impedance Calculation of the Power Distribution Network in Mobile Platforms," IEEE Transactions on Electromagnetic Compatibility, vol. 63, no. 3, pp. 912 - 921, article no. 9212604, Institute of Electrical and Electronics Engineers (IEEE), Jun 2021.
The definitive version is available at https://doi.org/10.1109/TEMC.2020.3026048
Electrical and Computer Engineering
Electromagnetic Compatibility (EMC) Laboratory
Keywords and Phrases
Design Methodology; Mobile Platform; Pattern-Based Analytical Modeling; Power Distribution Network (PDN); Via Inductance Extraction
International Standard Serial Number (ISSN)
Article - Journal
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01 Jun 2021