Simulation Analysis and Optimization for the Electromagnetic Susceptibility of Electronic Devices

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Simulation Analysis and Optimization for the Electromagnetic Susceptibility of Electronic Devices

更新时间：2025-07-09

- Simulation Analysis and Optimization for the Electromagnetic Susceptibility of Electronic Devices
- Vol. 44, Issue 8, Pages: 5-9(2010)
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN70;TP29
- Online First：10 August 2010，
  
  Published：2010
- 稿件说明：
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Simulation Analysis and Optimization for the Electromagnetic Susceptibility of Electronic Devices[J]. 2010, 44(8): 5-9.
DOI：

Simulation Analysis and Optimization for the Electromagnetic Susceptibility of Electronic Devices[J]. 2010, 44(8): 5-9. DOI：

摘要

提出了将高频电磁干扰环境中的电子设备作为整体来进行电磁敏感性仿真分析和优化设计的总体思路和分析方法.对于外部区域

改进已有的电磁散射的数值计算方法

在机壳表面采用四边形的片元模型代替已有算法中的三角形片元模型

重新定义电子设备外部区域面上的基函数

并根据机壳表面的对称关系对算法进行优化

减少了外部感应电流的运算时间.对于内部区域

利用基于微粒群优化算法的递归动态神经网络建立电子设备内部电路对于干扰的高频仿真模型

提出对于内部电路参数进行优化设计的方法.所建立的神经网络模型解决了以往电子设备在电磁敏感性仿真分析和优化设计过程中

仿真模型存在的计算量和存储量大的问题.优化设计方法改变了以往寻优过程中穷尽式搜索的方式.

Abstract

The overall thought and methodology of the simulation analysis and optimization for the electromagnetic susceptibility(EMS)of electronic devices in the industrial environment are proposed on account of high frequency electromagnetic interference. The existing numerical calculation method in electromagnetic scattering for external subdomains is modified

where the calculation time for external induced currents is reduced by replacing the original planar triangular surface patch modeling with the quadrilateral surface patch modeling on the enclosure surface. The basis functions on the external subdomain surface of electronic devices are redefined

and the algorithm is optimized based on symmetrical relation of the enclosure surface. For the internal subdomain

the dynamic recurrent neural network based on particle swarm optimization algorithm is employed to establish a high frequency simulation model of the interference for the internal circuit of electronic device. An optimization method for parameters of internal circuits is given based on the model. The problem of huge amount of calculations and storages in existing simulation models of EMS is avoided by the proposed neural model

and the conventional exhaustive search during optimization process is changed by the proposed optimization method.

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references

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