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Evolutionary Multiobjective T-Matrix Assisted Pin Map Optimization for Ball Grid Array Design
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DOI：10.1109/TEMC.2025.3621456.png)
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Abstract
En 中文
With the increasing operating frequency and integration density of ball grid array (BGA) packaging in high-performance systems, radiation leakage, and signal interference from solder balls in system-in-package (SiP) technology pose significant challenges. This article proposes an efficient optimization approach that integrates an extended T-matrix-based fast computation method with an enhanced multiobjective genetic algorithm (EMGA). The method addresses irregularities in pin diagram configurations and variations in packaging parameters, optimizing multisource shielding performance, and pin allocation counts. While minimizing design costs, it effectively reduces electromagnetic interference and enhances signal integrity, achieving an optimal arrangement. Scenarios demonstrate that the proposed algorithm excels in managing diverse variables and complex optimization objectives, offering improved efficiency, convergence, and robustness. Consequently, it provides a cost-effective solution for multisource self-shielding in BGA packaging, facilitating the design of reliable SiP systems.
Keywords:
Pins
Optimization
Electromagnetic compatibility
Noise
Electromagnetic interference
Packaging
Costs
Scattering
Genetic algorithms
Layout
Ball grid array packaging
computational electromagnetics
electromagnetic interference
genetic algorithm
multiobjective optimization
signal integrity
Journal
IF:
2.5
Papers:
115
Citations:
7.4K