Efficient Iterative Process Based on an Improved Genetic Algorithm for Decoupling Capacitor Placement at Board Level

Pcb Design For Real World Emi Control

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Effective PCB Decoupling Optimization by Combining an Iterative Genetic Algorithm and Machine Learning

Abstract: An iterative optimization for decoupling capacitor placement on a power delivery network (PDN) is presented based on Genetic Algorithm (GA) and Artificial Neural Network (ANN). The ANN is first trained by an appropriate set of results obtained by a commercial simulator. Once the ANN is ready, it is used within an iterative GA process to place a minimum number of decoupling capacitors for minimizing the differences between the input impedance at one or more location, and the required target impedance. The combined GA–ANN process is shown to effectively provide results consistent with those obtained by a longer optimization based on commercial simulators. With the new approach the accuracy of the results remains at the same level, but the computational time is reduced by at least 30 times. Two test cases have been considered for validating the proposed approach, with the second one also being compared by experimental measurements.

Genetic Algorithm PDN Optimization based on Minimum Number of Decoupling Capacitors Applied to Arbitrary Target Impedance

Abstract: 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.

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.

Advanced Signal Integrity for High-Speed Digital Designs

Abstract: Signal integrity has become the key issue in most high-performance digital designs. Now, from the foremost experts in the field, this book leverages theory and techniques from non-related fields such as applied physics, communications, and microwave engineering and applies them to the field of high-speed digital design. This approach creates an optimal combination of theory and practice that is meaningful to practicing engineers and graduate students alike.

Feature selective validation (FSV) for validation of computational electromagnetics (CEM). part I-the FSV method

Abstract: A goal for the validation of computational electromagnetics (CEM) is to provide the community with a simple computational method that can be used to predict the assessment of electromagnetic compatibility (EMC) data as it would be undertaken by individuals or teams of engineers. The benefits of being able to do this include quantifying the comparison of data that has hitherto only been assessed qualitatively, to provide the ability to track differences between model iterations, and to provide a means of capturing the variability and range of opinions of groups and teams of workers. The feature selective validation (FSV) technique shows great promise for achieving this goal. This paper presents a detailed analysis of the FSV method, setting it firmly in the context of previous comparison techniques; it suggests the relationship between validation of graphically presented data and the psychology of visual perception. A set of applicability tests to judge the effectiveness of computer-based CEM validation techniques is also proposed. This paper is followed by a detailed comparison with visual assessment, which is presented in Part II

Feature selective validation (FSV) for validation of computational electromagnetics (CEM). part II- assessment of FSV performance

Abstract: The feature selective validation (FSV) method has been proposed as a technique to allow the objective, quantified, comparison of data for inter alia validation of computational electromagnetics. In the companion paper "Feature selective validation for validation of computational electromagnetics. Part I-The FSV method," the method was outlined in some detail. This paper addresses two specific issues related to the implementation of the FSV method, namely "how well does it produce results that agree with visual assessment?" and "what benefit can it provide in a practical validation environment?" The first of these questions is addressed by comparing the FSV output to the results of an extensive survey of EMC engineers from several countries. The second is approached via a case study analysis

Genetic algorithms in electromagnetics

Abstract: The application of modern electromagnetic theory in real world radiation and scattering problems often requires or at least benefits from the use of optimization. This paper discusses a relatively new approach to the electromagnetic optimization problem called the genetic algorithm that can handle the common optimization problem characteristics with relative ease yielding near global maxima in cases that cannot be readily handled by any other optimization method.

Overview of Power Integrity Solutions on Package and PCB: Decoupling and EBG Isolation

Abstract: Mitigating power distribution network (PDN) noise is one of the main efforts for power integrity (PI) design in high-speed or mixed-signal circuits. Possible solutions, which are based on decoupling or isolation concept, for suppressing PDN noise on package or printed circuit board (PCB) levels are reviewed in this paper. Keeping the PDN impedance very low in a wide frequency range, except at dc, by employing a shunt capacitors, which can be in-chip, package, or PCB levels, is the first priority way for PI design. The decoupling techniques including the planes structure, surface-mounted technology decoupling capacitors, and embedded capacitors will be discussed. The isolation approach that keeps part of the PDN at high impedance is another way to reduce the PDN noise propagation. Besides the typical isolation approaches such as the etched slots and filter, the new isolation concept using electromagnetic bandgap structures will also be discussed.