任意目标阻抗下基于最小解耦电容数的遗传算法PDN优化

F. de Paulis, R. Cecchetti, C. Olivieri, Markus Buecker
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引用次数: 13

摘要

当前配电网络(PDN)设计的特点是去耦电容器的精确放置和其数量的最小化,以节省成本。本文提出了一种优化算法,用于相应地逐个放置去耦电容,并迭代评估每个PDN设计方案的成本函数。这样设计人员就可以确定输入阻抗满足目标阻抗要求时的最小电容数。该算法基于遗传算法,针对PDN的具体应用进行了相应的设计。它可能涉及多个位置的输入阻抗评估,代表多个IC,以及同一IC的多个电源输入区域/引脚。通过将开发的优化算法应用于制造的PCB并采用典型的(低电感)封装进行PDN设计,从而对其进行验证。优化过程产生了一种有效地考虑到封装值、寄生电感和封装位置的封装结构。精确的实验测试进一步验证了优化后的PDN。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic Algorithm PDN Optimization based on Minimum Number of Decoupling Capacitors Applied to Arbitrary Target Impedance
The current demand in Power Distribution Network (PDN) design is characterized by the accurate placement of decoupling capacitors and the minimization of their number aimed at cost saving. The paper proposes an optimization algorithm for accordingly placing decoupling capacitors one-by-one and iteratively evaluating the cost function of each PDN design solution. This allows the designer to identify the minimum number of decaps whenever the input impedance satisfies the target impedance requirements. The algorithm is based on the Genetic Algorithm accordingly adapted for the specific application of PDN design. It may involve the evaluation of the input impedance at multiple locations, representing either multiple ICs, as well as multiple power input areas/pins of the same IC. The validation of the developed optimization algorithm is carried out by applying it to a manufactured PCB and by employing typical (low inductance) decaps for PDN design. The optimization process led to a decap configuration that effectively takes into account the decap value, the parasitics inductance, and the decap location. An accurate experimental test further validates the optimized PDN.
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