HFSS在PCB共模滤波设计中
HFSS3微带滤波器教程
HFSS3微带滤波器教程
HFSS是一种强大的电磁仿真软件，用于设计和分析微波和射频电路。
本文将介绍如何使用HFSS设计和优化微带滤波器。
微带滤波器是一种常
见的射频和微波电路，用于选择性地传输或阻塞特定频率的信号。
下面是
设计微带滤波器的详细步骤。
第一步是确定所需的滤波器规格。
这包括中心频率、带宽、滤波器类
型和阻带衰减等参数。
根据这些参数，我们可以选择适当的滤波器结构。
第二步是建立HFSS模型。
首先，我们需要绘制滤波器的布局，包括
微带线、电容器和电感器等元件。
然后，根据需要调整元件的物理尺寸和
位置。
在HFSS中，我们可以使用其建模工具来完成这些任务。
第三步是设置HFSS模拟器。
我们需要选择仿真的频率范围和分辨率，并设置适当的激励条件。
通常，我们会使用端口激励来激励滤波器的输入端，并设置合适的端口阻抗。
第四步是运行仿真。
一旦设置好模拟器，我们可以运行仿真以计算滤
波器的S参数和其他性能指标。
在HFSS中，我们可以使用不同的分析工
具和图表来查看结果，例如频率响应图和阻带衰减图。
第五步是优化滤波器性能。
如果滤波器的性能不满足需求，我们可以
尝试不同的设计参数或结构，然后重新运行仿真来评估其性能。
通过多次
迭代优化，我们可以得到满足要求的滤波器设计。
最后，我们还可以进行进一步的分析，例如模拟温度效应、探索器件
的灵敏度和稳定性等。
这些分析可以帮助我们更好地理解滤波器的性能和
行为。
高速PCB差分过孔HFSS仿真分析与优化
高速PCB差分过孔HFSS仿真分析与优化信号完整性在高频高速电路中十分重要，差分过孔的不连续性会严重影响到信号的完整性，针对高速印制电路板(printed circuit board，PCB)中差分信号与共模信号对差分过孔的低反射、高传输和阻抗稳定的设计要求，首先建立差分过孔的等效物理模型与电路模型进行差分过孔的差分信号与共模信号的性能分析;然后在 PCB 层叠结构和布线模式设计的基础上运用三维电磁仿真软件HFSS 设置不同的过孔中心距、反焊盘直径及地过孔数量，对差分过孔的时域阻抗、回波损耗、插入损耗进行仿真与分析，并利用S 参数与时域内阻抗变化，分析过孔的差分性能和共模性能;最后通过仿真结果分析，得出过孔中心距38 mils(1 mil =0. 025 4 mm)、反焊盘直径 32 mils 及使用双过孔地过孔的设置使差分信号和共模信号的性能最优，提出优化了差分过孔的性能的新思路，为高速差分过孔设计提供参考。
引言在高速印制电路板(printed circuit board，PCB)设计中，由于差分结构相比于单端结构在信号完整性方面有很多优势，因此高速PCB 设计中常应用差分结构，差分过孔也广泛应用于连接不同层中的差分结构，虽然差分过孔使互连变得容易，但差分过孔的不连续性也会严重影响到信号完整性，因此研究差分过孔的特性非常重要。
分析差分过孔性能常常需要建立模型，目前已经进行了许多关于过孔建模的研究，但多集中于单过孔，而将单过孔外推至差分过孔仅在相邻过孔之间的电容和电感耦合可忽略不计时才有效，这个特征对于差分过孔并不适用，因此需要分析差分过孔的特性，从而建立适用于差分过孔的新型模型。
目前，对于差分过孔特性的分析和研究主要集中于过孔结构优化之上，文献研究了差分过孔短柱(Stub)如何影响时域传输(TDT)波形和眼图，并提出了一种带有/不带有额外通气孔的高阻抗差分优化方案以减轻差分过孔 stub 的影响。
基于HFSS的微带滤波器设计与应用
基于HFSS的微带滤波器设计与应用随着通信技术的不断发展，无线通信系统变得越来越普遍。
为了保证通信质量，必须对无线信号进行有效的过滤，因此滤波器成为了无线通信中最关键的组成部分之一。
基于微带技术的滤波器在无线通信中应用广泛，由于其体积小、重量轻、成本低、工艺简单的特点，在现代无线通信系统中依然扮演着不可替代的角色。
本文将基于HFSS软件，介绍微带滤波器的设计原理、设计流程、实现方法及其在无线通信中的应用。
一、微带滤波器的基本原理微带滤波器（Microstrip Filter）是一种基于微带线和附加衬底的元器件。
它通过在一条微带线（或几个相互交错的微带线）上挂载电容、电感和电阻等元件来实现滤波功能。
微带滤波器的基本结构如图1所示。
图1 微带滤波器基本结构图微带线的特性阻抗通常为50欧米，而微带滤波器需要特定的阻抗、通带和截止频带。
为了实现这些要求，滤波器需要在微带线模型上添加附加的元件来调整频率响应。
元件的安装可以使用多种方法，如串联、并联、交替安装等。
二、基于HFSS的微带滤波器设计流程首先需要明确滤波器的指标要求，包括通带和阻带的带宽、通带和阻带的中心频率、阻带衰减和通带波纹等参数。
这些指标根据具体应用需求而定，对于不同的应用场景可能存在较大差异。
2. 设计微带线结构在得到了所需的指标要求之后，需要根据这些要求设计微带线结构。
常用的方法是采用已有的文献或实验数据资料作为参考模板，进行修改和优化。
设计微带线时需要确定线宽、线距、衬底材料和厚度等参数，以实现所需的过渡阻抗和其他指标。
3. 添加补充元器件为了实现所需的频率响应，需要在微带线模型上添加各种补充元器件。
这些元器件包括电容、电感和电阻等，具体安装方式根据所需指标而定。
4. 模拟仿真使用HFSS软件进行微带滤波器的模拟仿真，得到滤波器的频率响应图和其他重要参数。
常规方法是在仿真软件中建立微带滤波器的三维模型，在模拟中通过修改材料参数、添加元器件、调整参数等方式进行仿真分析。
HFSS高性能平行耦合微带带通滤波器设计与仿真攻略
HFSS高性能平行耦合微带带通滤波器设计与仿真攻略实现射频带通滤波器有多种方法，如微带、腔体等。
腔体滤波器具有Q值高、低插损和高选择性等特点，但存在成本较高、不易调试的缺点，并不太适合项目要求。
而微带滤波器具有结构紧凑、易于实现、独特的选频特性等优点，因而在微波集成电路中获得广泛应用。
常用的微带带通滤波器有平行耦合微带线滤波器、发夹型滤波器、1/4波长短路短截线滤波器、交指滤波器等形式以及微带线的EBG (电磁带隙)、DGS(缺陷地结构)等新结构形式。
而平行耦合微带带通滤波器具有体积小、重量轻、易于实现等优点。
01平行耦合带通滤波器的基本原理平行耦合带通滤波器是一种分布参数滤波器滤波器，它是由微带线或耦合微带线组成，其具有重量轻、结构紧凑、价格低、可靠性高、性能稳定等优点，因此在微波集成电路集成电路的供应商中，它是一种被广为应用的带通滤波器。
滤波器的基础是谐振电路，它是一个二端口网络，对通带内的频率信号呈现匹配传输，对阻带频率信号失配而进行发射衰减，从而实现信号频谱过滤功能。
微波带通滤波器在无线通信系统通信系统中起着至关重要的作用，尤其是在接收机前端。
滤波器性能的优劣直接影响到整个接收机性能的好坏，它不仅起到频带和信道选择的作用，而且还能滤除谐波，抑制杂散。
02平行耦合带通滤波器结构与模型的创建平行耦合带通滤波器原理平行耦合单元由两根相互平行且有一定间距的微带线组成，其结构图包括介质层、接地层和微带线如图 3.3 所示。
图中每根微带线的宽度和厚度分别为为W 和t；两根微带线的间距为S；介质层厚度和介电常数分别为h 和Er。
两根微带线通过接底层产生了耦合效应，随之产生了奇模和偶模特征阻抗。
平行耦合带通滤波器通过级联平行耦合线元件得到。
平行耦合带通滤波器的相对带宽BW 与中心频率、上边频和下边频有关，而奇模和偶模特征阻抗由低通滤波器参数g、滤波器输入输出端口特征阻抗Zo和耦合单元组成。
可由以下公式得到：平行耦合带通滤波器参数计算与设计本节中所设计的平行耦合带通滤波器指标如下表所示：根据表中滤波器指标，选择0.1dB纹波的切比雪夫滤波器来设计，阶数为5阶。
HFSS分析小型化微带滤波器
用Ansoft HFSS 分析小型化、高带外抑制的微带滤波器赵 平上海航天局八0四研究所电子三室 200082摘要：本文用Ansoft HFSS 分析小型、高带外抑制的PBG 结构的微带滤波器的结构形式和特有的频率响应特性。
关键词： PBG 光子带隙结构 Ansoft HFSS 微带 带通滤波器1. 引言随着“无线时代”的到来，微波工程师关注于电磁波频谱合理、高效、安全的使用、EMI / EMC 问题的解决，小型化、高带外抑制、低成本、宽带滤波器的研究、应用有着重要的意义。
微波滤波器已成为无源微波元件的主角之一，它不仅能完成本身的任务，而且能代替其他一些微波元件的功能，或者可把另外一些微波元件看成微波滤波器结构来进行设计，随着新材料、新技术的引入、应用，滤波器的概念“广义化”。
2. 滤波器设计2.1 滤波器响应函数类型选择图2 1994年 Alumina 构建的光子晶格滤波器特性可用其频率响应来描述，按其特性的不同可分为低通滤波器、高通滤波器、带通滤波器、带阻滤波器。
图1中是以带通滤波器为例的滤波器响应，图中横坐标是归一化频率f，纵坐标是工作衰减（简称“衰减”）或插入衰LA 。
图 1 中所示三种函数滤波器的传输特性，观察可知不同点在于传输零点的位置： Chebyshev 函数滤波器传输零点在无限远处，Elliptic 函数滤波器传输零点在有限特定频率且阻带呈现等波纹特性，Quasi-Elliptic 函数滤波器将 hebyshev 函数滤波器和 Elliptic函数滤波器的特性“融合”在一起：即保留了无限远处的零点，又有一对传输零点在特定频率。
由此分析，可得出关于滤波器类型选择的依据：为了满足通带的插入损耗带外隔离，应选级数较少的滤波器，相应的级数较少的滤波器的Q 值也低；通带边沿的插入损耗期望等同于通带中心频率的插入损耗，在 Elliptic 函数滤波器、Quasi-Elliptic 函数滤波器中通带边沿的插入损耗受截至频率附近的传输零点影响较大；Chebyshev 函数滤波器和 Elliptic 函数滤波器、Quasi-Elliptic 函数滤波器相比 ，虽然带外隔离较好，但在靠近通带边沿处比选择性差；虽然可以通过增加级数提高选择性，但同时带内插入损耗也增加；Elliptic 函数滤波器在靠近通带边沿有较高的选择性，但是相对于 Quasi-Elliptic 函数滤波器，它的带外隔离较差；Elliptic 函数滤波器应用分布元件较难实现，而 Quasi-Elliptic 函数滤波器却较之容易满足设计要求。
基于ADS和HFSS低通滤波器设计与仿真
低通滤波器设计指标：
具有最平坦响应 截止频率fc=3.0GHz 在f=4GHz处，插入损耗IL(S21)<-15dB 在通带内（0-3GHz），回波损耗S11≤-15dB 输入输出阻抗为50Ω，采用6阶巴特沃斯低通原型 采用FR4板材，板厚1.58mm，介电常数εr=4.4，损耗角
XY Plot 2
LPF-Original
0.00
m1 Curve Info
m2
dB(S(2,1))
Setup1 : Sw eep -5.00
Name X Y
从图中可以得到，滤波器
-10.00
m1 2.7400 -1.5064
m2 3.0000 -4.0389
-15.00
m3 4.0000 -20.0776
从图中可以得到，滤波器在
3.0GHz就开始截止了，达到设计指 标 ， 在 4GHz 处 ， S21=-12.139dB 符 合设计要求。
综上所述，该滤波器已经完全达到设计指标，此时各节微带线 长度与宽度如下表所示：
节数 1 2 3 4 5 6 7 8
W(mm) 3.41 12.74 0.34 10.60 0.50 9.84 0.30 3.41
θ(°) 90 11.8 33.8 44.3 46.1 32.4 12.3 90
W(mm) 3.01 11.05 0.36 11.05 0.36 11.05 0.36 3.01
L(mm) 16.45 2.02 6.64 7.58 9.05 5.54 2.42 16.45
ADS仿真：
根据设计计算得到的微带线尺寸在ADS构建低通滤波器电路如下：
将搭建好的低通滤波器电路运行仿真得到数据： 从图中可以看到，S11和S22小于-15dB带宽范围为0-1.8GHz，远没有 达到设计指标。
HFSS高性能平行耦合微带带通滤波器设计与仿真攻略
HFSS高性能平行耦合微带带通滤波器设计与仿真攻略HFSS（High Frequency Structural Simulator）是一款广泛应用于高频电磁场仿真的软件工具，具有高效准确的计算能力，广泛应用于微波通信、天线设计、微带滤波器设计等领域。
在微带带通滤波器设计中，HFSS软件可以帮助工程师快速准确地设计出性能优异的滤波器，提高设计效率和准确性。
本文将介绍HFSS软件在高性能平行耦合微带带通滤波器设计与仿真中的一般步骤和攻略。
一、平行耦合微带带通滤波器原理平行耦合微带带通滤波器是一种结构简单、性能良好的微带滤波器，通常由一组垂直耦合微带谐振器和几个开路微带谐振器组成。
通过合理设计电路结构中的微带谐振器的长度、宽度和耦合间隔等参数，可以实现所需的滤波特性。
平行耦合微带带通滤波器通常具有较低的插入损耗、较高的带宽和较好的阻带衰减等性能。
二、HFSS平行耦合微带带通滤波器设计步骤1.确定滤波器的工作频率和性能指标，如通带中心频率、通带带宽、阻带衰减等；2.设计滤波器的电路拓扑结构，包括微带谐振器的种类和数量、耦合方式等；3.利用HFSS软件建立滤波器的三维模型，并设置仿真参数，如工作频率、网格精度等；4.通过HFSS软件进行电磁场仿真，分析滤波器的传输特性和谐振器的工作状态，调整设计参数以满足性能指标；5.优化滤波器的结构设计，如微带谐振器的长度、宽度和耦合间隔等参数；6.在HFSS软件中进行频域和时域仿真，验证滤波器的性能指标是否满足设计要求；7.在满足性能指标的前提下，进一步优化滤波器的结构设计，以降低损耗和提高性能；8.导出最终的滤波器设计文件，用于制作和验证实际器件性能。
1.合理选择HFSS软件版本和许可证类型，确保软件功能和性能满足设计需求；2.熟练掌握HFSS软件的操作界面和基本功能，包括建模、设置仿真参数、网格划分、分析结果等；3.在建立滤波器的三维模型时，注意设计精度和模型简化，提高仿真效率和准确性；4.在仿真过程中，结合HFSS软件的参数优化功能，快速有效地调整设计参数，实现滤波器性能的优化；5.结合HFSS软件的频域和时域仿真功能，全面分析滤波器的传输特性和动态响应，确保性能指标的准确性；6.在滤波器设计的不同阶段，及时保存和备份仿真文件和结果，方便后续验证和分析；8.最终，通过HFSS软件的仿真和验证结果，确定滤波器的结构设计方案，并导出制作文件进行实际器件的制作和测试。
基于HFSS设计同轴腔滤波器
第30卷 第2期2007年4月电子器件Chinese J ournal Of Elect ron DevicesVol.30 No.2Ap r.2007Design of Coaxial Filters B ased On HFSSL I U Pen g 2y u1,2,Z H A N G Yu 2hu 2,S H EN H ai 2gen11.School of Elect ronic I nf ormation and Elect ric Engineering ,S hanghai J iao Tong Universit y ,S hanghai 200240,China;2.S hanghai S pacef li ght I nstit ute of T T &C and Telecommuniation ,S hanghai 200086,Chi naAbstract :Coaxial filters is widly used in microwave circuit s.we research how to analysis and design coaxial filters used by a 3D f ull 2wave field solver ,HFSS.The 3D f ull -wave field analysis includes t he effect s of t uning screw ,interstage coupling apert ure and inp ut/outp ut coaxial excitation.Base on t hess analysises ,we work out a S -band coaxial filter aided by simulating and optimizing in HFSS.The result of t he experi 2mentation matched well wit h t he result of simulation ,and f ulfiled technic target s.The coaxial filter has been used in a spaceflight project successf ully.The way of combining t he t raditional t heory wit h t he ad 2vanced comp uter technology has great practical value ,it can save much time and co st .K ey w ords :microwave filters ;coaxial resonator ;coupling apert ure ;HFSS EEACC :1320基于HFSS 设计同轴腔滤波器刘鹏宇1,2,张玉虎2,沈海根1(1.上海交通大学电子信息与电气工程学院,上海200240;2.上海航天测控通信研究所,上海200086)收稿日期:2006204217作者简介:刘鹏宇(19782),男,工作于上海航天测控通信研究所,工程师,主要研究方向为射频与微波电路设计,pengyu_liu @ ;摘 要:同轴腔滤波器在微波电路中有着广泛的应用,在此研究如何利用3D 全波场分析软件HFSS 分析设计同轴腔滤波器.该分析包括谐振腔调谐螺钉、腔间耦合孔及输入输出激励的影响效应.基于上述分析,借助HFSS 仿真优化得到一S 波段滤波器.其实测结果与仿真相符,满足指标要求,并已成功应用于某航天工程中.这种结合传统理论和先进计算机技术的方法可以大大节省研制周期和生产成本,具有非常大的实用价值.关键词:微波滤波器;同轴谐振腔;耦合孔;HFSS 中图分类号:TN 713 文献标识码:A 文章编号:100529490(2007)022******* 传统的微波滤波器设计方法已经非常成熟,但其中一些参数需要反复试验来获得.这势必要增加产品的设计周期,对于当前研制周期紧、产品数量大的要求是一个制约.利用仿真工具进行辅助设计成为目前一种非常有效的解决途径.本文即介绍如何借助H FSS 设计同轴腔滤波器.1 HFSS 简介HFSS 是ANSO F T 公司开发的一个基于物理原型的EDA 设计软件.使用H FSS 建立结构模型进行3D 全波场分析,可以计算.①基本电磁场数值解和开边界问题,近远场辐射问题;②端口特征阻抗和传输常数;③S 参数和相应端口阻抗的归一化S 参数;④结构的本征模或谐振解.依靠其对电磁场精确分析的性能,使用户能够方便快速地建立产品虚拟样机,以便在物理样机制造之前,准确有效地把握产品特性,被广泛应用于射频和微波器件、天线和馈源、高速IC 芯片等产品设计中.H FSS 有本征模解(Eigenmode Solution )和激励解(Driven Solution )两种求解方式.选择Eigen 2mode Solution 用于计算某一结构的谐振频率以及谐振频率点的场值和腔的空载Q0值.选择Driven Solution用于计算无源高频结构的S参数和特性端口阻抗、传播常数等.本课题的研究中,将用到本征模解求解单同轴腔特性和腔间耦合系数;激励解求解有载品质因数Q L值和滤波器响应特性.2 同轴腔滤波器工作原理及设计2.1 工作原理同轴腔滤波器主要用于米波、分米波段.传输TEM模,无色散、场结构简单稳定、空载品质因数高[1].其基本结构由谐振腔、腔间耦合、输入输出激励组成,如图1所示即为一个三腔同轴滤波器.输入信号通过闭合圆环耦合到谐振腔中产生谐振,能量在谐振腔之间由耦合孔进行逐级耦合,再经图1 三腔同轴滤波器结构模型(a=3.25mm,b=9mm,l=29mm,l1=l2=14mm)过输出端的闭合圆环耦合输出.各腔均工作在同一谐振频率附近,只有该谐振频率附近的电磁波有效传输,形成一带通滤波器.2.2 集总参数网络设计下面以S波段滤波器设计为例,主要技术指标见表1.表1 滤波器技术指标技术参数工作频率f0插入损耗L A带宽(4f3dB)通带波动L Ar阻带抑制L As(f0±15M Hz)输入输出阻抗Z o指标要求2.0～2.15GHz≤2dB≥8M Hz≤±0.3dB≥25dB50Ω 利用网络综合法[2],选取切比雪夫函数作为逼近函数,查表或计算[3]确定滤波器阶数n=3,对应的低通原型参数:g0=g4=1,g1=g3=1.0316,g2=1.1474,由此得到腔间耦合系数K ij和外部品质因数Q L.K ij=bwg i・g j=0.0036(i=1,j=2;i=2,j=3)(1)Q L=g1bw=266.3(2)2.3 微波结构设计2.3.1 同轴腔为减小体积和便于安装,本滤波器采用内圆外方的1/4λ缩短电容同轴腔结构.依据谐振腔结构尺寸参数选取三个原则[1]:①避免高次模,(a+b)≤λmin/π;②满足功率容量,b/a=1.65时功率容量最大;③损耗要小,b/a=3.6时Q0值最高,损耗最小.b/a一般选择在2.0～3.6之间.在此选取内导体半径a=3.25mm,外导体内半径b=9mm.内导体长度l、调谐螺钉最大调谐距离t的设计既要考虑能够满足所需的调谐范围,同时还要考虑到内导体缩短会降低Q0值[4]的因素,一般选择内导体长度为1/4λ的65%以上,在此选取l=29mm,t=3mm.谐振腔的调谐范围将通过HFSS进行仿真验算.2.3.2 耦合考虑到本滤波器属于窄带滤波器,腔间耦合[5]采用圆孔实现,输入输出耦合采用闭合半圆环实现.耦合圆孔、半圆环需要确定的参数是中心位置和半径大小.滤波器带宽基本上由级间耦合决定.设计一个在某个频率范围内可调谐的滤波器时,若要保持固定的带宽,则必须控制带宽对频率的敏感性,即要保持d(Δf)/d f=0.Cohn[6]研究得出,当耦合孔中心离腔短路端距离l1在中心频率电长度36°附近时,耦合带宽最大且随频率变化缓慢.则取l1=14mm.半圆环的几何位置通常与耦合孔保持一致,所以也取l2=14mm.关于耦合孔径的大小,下面通过HFSS仿真腔间耦合系数K ij和外部品质因数Q L获取.3 HFSS仿真分析3.1 单谐振腔仿真根据选定的结构尺寸(a=3.25mm,b=9mm, l=29mm),在H FSS中对单谐振腔建模(图2),不需要加载激励,进行Eigenmode分析,获取在不同间距t的加载电容下对应的谐振频率.仿真结果(图3)得出,当t在0.25～3mm之间调整,对应谐振频率范围在1619～2171M Hz之间变化,可以满足要求.图2 单谐振腔模型 图3 谐振频率与加载电容关系3.2 腔间耦合系数K ij仿真腔间耦合的电性能用耦合系数K ij表示.当两134第2期刘鹏宇,张玉虎等:基于H FSS设计同轴腔滤波器个相邻的谐振腔耦合在一起、并且对源和负载具有非常小的耦合时,K ij 与相邻腔谐振频率f 1、f 2存在如下关系[7]:K 12=2(f 2-f 1)/(f 2+f 1)(3)因此,对两个相邻谐振腔在不接源和负载(图4)情况下进行Eigenmode 分析(modes =2),得到在不同圆孔半径下对应的谐振频率f 1、f 2,从而绘制出对应的腔间耦合系数曲线(图5).结果表明耦合孔越大,耦合越强.图4 腔间耦合系数仿真模型图5 耦合圆孔与耦合系数关系3.3 有载品质因数Q L 仿真当单个谐振腔耦合源和负载时,有载品质因数Q L 与谐振频率f o 及3dB 带宽Δf 3dB 存在如下关系[7]:Q L =f o /Δf 3dB(4)建立模型对单谐振腔加载源和负载(图6),进图6 有载品质因数 图7 耦合圆环与有载品质仿真模型因数关系行Driven Terminal 分析,得到在不同耦合圆环半径下对应的有载品质因数Q L 曲线(图7).耦合环越大,耦合越强,Q L 值越低. 根据公式(1)、(2)中计算结果,对照以上仿真分析图表,即可选取适当的结构参数,在H FSS 中完成整个滤波器的建模(图1),经过进一步优化,获取理想的特性曲线,确定最终的结构尺寸:r _apert ure =3.18mm ,r _loop =2.6mm .4 实测结果与分析综合上述设计及优化结果,并考虑到为实物调试时留有一定的调整余量,耦合孔和耦合环半径均取的略小一些,确定最终的加工尺寸见表2.表2 同轴腔滤波器结构加工尺寸结构参数a bltl 1l 2r _loop r _aperture尺寸/mm 3.25929314142.53 按照表2结构尺寸机械加工,进行适当的谐振频率和耦合调整,获得了满意的特性曲线(图8),达到技术指标要求(表3).结果表明,插入损耗、带外抑制实测结果比与仿真结果要差一些.这是可以理解的,因为HFSS 仿真是在理想边界条件下进行的,而滤波器实物是由三个单谐振腔和输入输出端口组合在一起的,,还有腔体内部镀银表面不光滑,这些都会引入损耗[8],导致Q 0值降低,使得插损、带外抑制指标略有变差.图8 实测(粗线)与仿真(细线)滤波器响应表3 滤波器测试数据技术参数工作频率f 0插入损耗L A带宽(Δf 3dB )通带波动L Ar 阻带抑制L A s(f 0±15M Hz )驻波比指标要求2.065GHz 1.75dB8.5M Hz 0.15dB33.6dB1.345 结束语本文利用ANSO F T HFSS 仿真软件对同轴腔滤波器中的谐振腔、腔间耦合及输入输出激励进行了优化设计,确定了滤波器实际结构尺寸,测试结果与仿真一致.该方法可以有效并准确地替代传统试验方法,也可以应用在其它的微波滤波器设计中.参考文献:[1] 廖承恩,陈达章.微波技术基础[M].北京:国防工业出版社,1979.[2] 甘本,吴万春.现代微波滤波器的结构与设计[M].北京:科学技术出版社,1973.[3] Hong Jia 2Sheng.Microstrip Filters for RF/Microwave Applications ,ncaster C opyrightc 2001John W illy &S ons ,Inc.pp.29261.[4] K urzrok R.M.Design of C omb 2Line Band 2Pass Filters (C orrespon 2dence )[J ].T ransactions on Microwave Theory and T echniques ,Jul.1966,T 2MTT 214(7):3512353.[5] 姚毅,黄尚锐.调谐滤波器的腔间耦合结构研究[J ].微波学报,1994(1):16222.[6] K urzrok R M.Design of Interstate C oupling Apertures for Narrow 2Band T unable C oaxial F ilters[J ].(C orrespondence )IRE T rans.on M i 2crowave ’Theory and T echniques ,March ,1961,MTT 210:1432144.[7] Randall W.Rhea ,HF Filter Design and Computer Simulation[M ].Mc Graw 2Hill ,Inc.,1995.[8] 高葆新.波导带通滤波器的设计[J ].国外电子测量技术,2001(1):34237.234电 子 器 件第30卷。
在HFSS中完成PCB与三维器件的联合仿真
-15.00 0.00
10.00
20.00
Freq [GHz]
30.00
40.00
50.00
获取最终系统的仿真结果
总结
➢ 板级全波电磁场的系统级仿真推向了新的高度 ➢ 同时考虑三维实体器件，集总器件和PCB本身 ➢ 完全集成于HFSS 3D LAYOUT环境 ➢ 灵活的求解技术选择
Ansoft LLC 0.00
self ind S Pl
-2.50
-5.00
S Parameter in db
-7.50
-10.00
-12.50
Curve Info
dB(S(P1,P2)) self ind
dB(S(STRIPLINE_SYMMETRIC_PERFORATED_PLANE_A_0_T1,STRIPLINE_SYMMETRIC_PERFORATED_PLANE_A_0_T2)) Import1
建立三维器件 的HFSS模型
在HFSS 3D LAYOUT 中导入PCB并设置端口
为PCB上的集总 RLC器件建模
动态链接 HFSS模型
为PCB仿真选择 求解器和扫频范围
系统线性网络 协同仿真
端口与网络映射
放置三维器件的 布局与旋转
通过3D Component建立HFSS三维模型
HFSS内置了若干常见3D Component库
在HFSS 3D LAYOUT中完成PCB与三维器件联合仿真
Agenda
• 3D Components • HFSS 3D LAYOUT • Layout Driven System Verification
Assembly of 3D Components
HFSS和serenade滤波器设计
Efficient Design of Chebychev Band-Pass Filters with Ansoft HFSS and SerenadeTutorialDr. B. Mayer and Dr. M.H. VogelAnsoft CorporationContentsAbstract 31. Introduction 32. Circuit Representation of the Filter 53. Relationships between Circuit Components and Physical Dimensions in the Microwave Filter 104. Initial Filter Design in HFSS 145. Curve Fitting in Serenade 166. Corrected Filter Design in HFSS 207. Additional Information from the 3D Field Solver 21 7a. Effects of Internal Losses 21 7b. Maximum power-handling capability 23 7c. Mechanical Tolerances 24 References 25 Appendix A Derivation of the Circuit 26 Appendix B The Physical Meanings of K and Q 43AbstractAn efficient method is presented to design coaxial Chebychev band-pass filters. The method involves a 3D full-wave field solver, Ansoft HFSS, teaming up with a circuit simulator, Serenade. The authors show how for a practical case, a 7-pole band pass filter with a ripple of only 0.1 dB, an accurate design is obtained in a matter of days, as opposed to weeks for traditional methods.The method described is also applicable to even more challenging designs of elliptic filters and phase equalizers realized in dielectric, waveguide or coaxial technology.1 IntroductionIn this paper, we will describe an efficient method to design a filter. The method involves a 3D full-wave field solver teaming up with a circuit simulator. The basic idea has been explored by others [1] but a different circuit was used in the circuit simulator. We will explain our procedure by presenting in detail how we design a Chebychev band pass filter with the following specifications:Center frequency 400 MHzRipple bandwidth 15 MHzRipple 0.1 dBOut-of-band rejection 24 dB at 390 MHz and at 410 MHzIn order to achieve the out-of-band rejection, we will need seven poles.The desired filter characteristic is shown in Fig. 1.Fig. 1 Desired filter characteristicAs the basic geometry for this filter we have chosen a cavity with seven coaxial resonators, as shown in Fig. 2. In the figure, the “buckets” have been drawn as wire frames for clarity, to show that the cylinders don‟t extend all the wa y to the bottom.Fig. 2 Basic filter geometryThis geometry is symmetrical with respect to the central cylinder. In this kind of filter, the walls of the cavity, the long cylinders, the buckets under the cylinders and the disk-shaped objects near the first and last cylinder are all made of metal. The long cylinders are connected to the top of the cavity; the buckets are connected to the bottom of the cavity. Cylinders and buckets don‟t touch. The disk-shaped objects near the first and last resonator are connected to the input and output transmission lines and provide the necessary coupling to the source and the load. We will call these objects antennas in this document. They are near the first and last cylinders, but never touch them. Each cylinder-bucket combination is a resonating structure. At this stage, without restricting ourselves, we can choose many dimensions in the filter relatively freely. We make the following choices:Cavity dimensions 280 x 30 x 120 mmResonator diameter 10 mmBuckets‟ inner diameter12 mmBuckets‟ outer diameter 16 mmBuckets‟ height15 mmAntennas‟ diameter26 mmAntennas‟ thickness 6 mmSix dimensions remain, and these six will be crucial in obtaining the desired filter characteristic:The length of the first and last resonating cylinder (both have equal length)The length of the five interior cylinders (all five have equal length)The distance between an antenna and its nearest cylinderThree distances between neighboring cylinders (remember the filter is symmetric) With traditional filter design methods, obtaining the correct dimensions is a time-consuming task that commonly takes several weeks. Filter design with a circuit simulator, on the other hand, is relatively straightforward. Filter theory provides the values for the lumped inductors and capacitors that are needed to obtain the desired filter characteristic. First, we will show how to design a circuit that not only has the desired filter characteristic, but also lends itself to implementation with microwave components. In such a circuit, we use series L and C for each resonator, i.e. the cylinder-and-bucket combinations, and impedance invertors to represent the distances between adjacent resonators. Second, we will show how one can determine relationships between components in the circuit and dimensions in the physical filter. Third, we will present an iterative procedure between the electromagnetic field solver and the circuit simulator to optimize the design. The procedure converges very quickly.2 Circuit Representation of the FilterIn order to design an order-seven band-pass filter around 400 MHz with a 0.1 dB ripple, filter theory tells us to start with an order-seven low-pass filter, normalized to 1 radian/s. The normalized filter is to have a 0.1 dB ripple, like the desired band pass filter. The source and load impedances of the normalized low pass filter are normalized to 1 Ohm. This circuit is shown in Fig. 3 and its characteristic in Fig. 4. Filter theory provides us with the values for the inductors and the capacitors, denoted by g1 through g7 in the figure. These values are in our caseg1=g7=1.1812 Hg3=g5=2.0967 Hg2=g6=1.4228 Fg4=1.5734 F.Fig. 3 Normalized low-pass filter circuit, starting point for design procedureFig. 4 Filter characteristic for the normalized low-pass filter in Fig. 3The step-by-step procedure from this normalized low-pass filter circuit to the final band-pass filter circuit is presented in detail in Appendix A. Here, we show an outline of the major steps.An important step is the replacement of shunt capacitors by series inductors and impedance inverters. Basically, an impedance inverter transforms impedances in the same way as a quarter-wave-length transmission line, but independent of frequency. The resulting circuit is shown in Fig. 5. This is still a normalized low-pass filter with the same characteristic as the circuit in Fig. 3. The reason for this change is that at microwave frequencies it is often impossible to realize the ladder circuit consisting of series inductors and shunt capacitors. Depending on the basic structure either series elements or shunt elements are easily realizable but often not both in the same structure. Taking advantage of impedance inverters, it is possible to transform shunt capacitors into series inductors. In the physical filter these impedance inverters will be realized by couplings between the coaxial resonators.Fig. 5 Normalized low-pass filter without shunt capacitorsFollowing a standard procedure, we take the following steps to derive the desired band-pass filter model:(1)De-normalize the low-pass cut-off angular frequency from 1 rad/s to bw rad/s.(2)Transform the low-pass filter to a band-pass filter with a relative bandwidth ofbw and a center angular frequency of 1 rad/s by inserting a 1 F capacitor inseries with every 1 H inductor.(3) De-normalize the center frequency to 400 MHz by choosingL=1/(2×π×4E8) H and C = 1/(2×π×4E8) F.(4) De-normalize the port impedances from 1 Ohm to the usual 50 Ohm byintroducing impedance inverters at the input and output with coupling coefficients of √50.(5) Introduce finite quality factors to the individual resonators by adding a seriesresistor to each resonator.(6) Introduce individual resonant frequencies to the first and last resonators to beable to be able to take the frequency shift due to the coupling antennas intoaccount.(7) Add a homogeneous transmission line of length ZUL between filterinput/output and port 1 / port 2 to be able to adjust the phase due to the connectors. This gives us the filter shown in Fig. 6. The procedure outlined above is presented in more detail in Appendix A.Fig. 6 Final filter circuit, representing the desired band pass filterIn this circuit, every LC pair resonates at 400 MHz. Further K12, K23, K34 and Q L have been defined asK ij= bwg i g j(1)andQ= g1bw(2)where bw is the relative bandwidth and g i is the i th g value from filter theory.Notice that, since the g values are known from filter theory, we still know the values of the all the components in the circuit, even through the components have changed considerably in the process.Filter theory [2] tells us that K i,i+1 and Q L have important physical meanings. K i,i+1 is known as the coupling constant between adjacent resonators. If we have just two resonators in the cavity, with a very light coupling to the source and the load, then the relation between coupling constant K12 and resonant frequencies f1 and f2 is given byK12 = 2(f2-f1) / (f2+f1) . (3)Q L is known as the loaded Q of the circuit. If we have just one resonator in the cavity, coupled to source and load, the relation between Q L , resonant frequency f R and 3-dB band width BW3dB is given byQ L = f R / BW3dB(4)In the next section, we will link the components of this circuit to dimensions in the physical geometry of the filter.3 Relationships Between Circuit Components and Physical Dimensions in the Microwave FilterAs explained in the previous section, every LC pair resonates at 400 MHz. In the microwave filter, we must choose the length of each resonator such that it resonates at 400 MHz. That will determine the length of each of them.Further, K i,i+1 (i=1,2,3) are the coupling coefficients between adjacent resonators. Therefore, these three coefficients are related to the distances between adjacent resonators.Finally, Q L is the loaded Q of the circuit. Therefore, in an otherwise lossless circuit, it is directly related to the distance between the first or final resonator and the antenna that couples it to the source or the load.3a Relation Between Resonator Spacing and Coupling CoefficientThe model in Ansoft HFSS that was used to determine the coupling coefficient K as a function of resonator spacing is shown in Fig. 7. Two resonators have been placed in a closed metal cavity. This cavity has the same height and the same front-to-back depth as the cavity to be used in the real filter. The left-to-right width has been chosen large enough to make its influence on the results negligible. There are no transmission lines nor ports for signal input and output, since the resonances of this structure are to be determined through an eigenmode simulation. In the Setup Materials menu, resonators are modeled as perfect conductors; the cavity is filled with air. Further, symmetry has been exploited through the use of a Perfect-H boundary condition. As can be seen in the figure, this cuts both the resonators and the cavity in half.Fig. 7 Model used to determine the coupling coefficient KBy embedding this HFSS project in Optimetrics, dimensions can be varied easily. First, the length of the cylinders was adjusted such that the resonances are centered at 400 MHz. Then, the distance between the resonators was varied, and for each distance the eigenmode solver in HFSS computed the two eigen frequencies and obtained K. In order to get very accurate results, more accurate than necessary, twelve adaptive passes were run in each simulation, resulting in models with 63,000 tetrahedra. Total run time foreach point was 38 minutes on a 1.2 GHz PC. The simulation of the lossless structure required 557 MB of RAM. The relation between the resonator spacing and K is shown graphically in Fig. 8.Fig. 8 Relation between resonator spacing and coupling coefficient K With this graph, for any coupling coefficient required by filter theory, the spacing to be applied between resonators in the physical model can be readily determined.3b Relation Between Antenna Distance and Loaded Q The model in Ansoft HFSS that was used to determine the loaded Q as a function of antenna spacing is shown in Fig. 9. An antenna-resonator combination has been placed in a closed metal cavity. The 50-Ω transmission line is present, but in order to perform an eigenmode analysis, it has been terminated by a Perfectly Matched Layer (PML) of absorbing material. This was done by replacing the final 20 mm of dielectric in the coaxial cable by PML material. A macro, named pmlmatsetup, in the Materials-Setup menu supplies the material parameters. This construction will give use the same resonant frequency and loaded Q as the corresponding structure with a real 50-Ω load would. The cavity has the same height and the same front-to-back depth as the cavity to be used in the real filter. Again, the left-to-right width has been chosen large enough to make its influence on the results negligible, and symmetry has been exploited through the use of a Perfect-H boundary condition.Fig. 9 Model used to determine the loaded QThis HFSS project has been embedded in Optimetrics. The antenna distance and the cylinder length were varied simultaneously, since both influence the resonant frequency and the loaded Q. As an example of the results, the relation between antenna spacing and loaded Q is shown graphically for a constant cylinder length of 113.4 mm. In order to get very accurate results, maybe a little more accurate than strictly necessary, fifteen adaptive passes were run for each point. This results in simulations with 50,000 tetrahedra, requiring 830 MB of RAM. Total run time per point was 50 minutes on a 1.2 GHz PC.Fig. 10 Relation between antenna spacing and loaded Q at a resonator length of 113.4 mmWith results like these, for any loaded Q and resonant frequency required by filter theory, the antenna spacing and cylinder length to be applied in the physical model can be readily determined.4 Initial Filter Design in HFSSNow that we have the circuit and we know the relations between circuit components and physical dimensions, we can construct the filter in the field solver, Ansoft HFSS. Filter theory tells us we need to achieve the following parameters: Resonant frequency of the outermost resonators f R1= 400 MHzResonant frequency of the inner resonators f R2=400 MHzLoaded QCoupling coefficients K12=0.02893 , K23=0.02171 , K34=0.02065The calibration projects above tell us that the dimensions of the filter, as shown in Fig. 2, are to beLength of the two outermost resonators = 113.399 mmLength of the five inner resonators = 114.69 mmAntenna distance = 1.879 mmDistances between resonators are 25.513 mm , 28.291 mm , 28.767 mmThis filter has been modeled and simulated in Ansoft HFSS. The model is shownin Fig. 11.Fig. 11 Initial design in HFSSNotice that only half the geometry is actually simulated. Symmetry has been exploited through the use of a Perfect-H boundary condition. Further, all materials and boundaries in the model are lossless for now. This requires less RAM and less CPU time. The resulting filter characteristic is shown in Fig. 12. Notice that the center frequency and the ripple bandwidth are almost perfect. We see the correct number of ripples, but theripple is 0.3 dB rather than 0.1 dB.Fig. 12 S21 results for the initial design in HFSS5 Curve Fitting in SerenadeThe HFSS results, shown in the previous section, have been exported to Serenade, the circuit simulator. This was done through Post Process / Matrix Data / File / Export / Touchstone. In Serenade, we can determine through curve fitting what the actual parameters of this initial design are. This curve fitting is done through the Serenade setup shown in Fig. 13. All the variables are defined in the top level schematic. Circuit model and HFSS results are defined via the sub circuits denoted as MODEL and MEASU, respectively. To utilize all the available information for the optimization process, the optimization goal is to end up in a complex S-Matrix identical for the model and the S-matrix resulting from the HFSS simulation. This is defined in Serenade via an OPT block and the goal definition S=MEASU in the sub circuit defining the circuit model as shown in Fig. 14. To match the phases of the S parameters of the Serenade and HFSS simulations, homogeneous transmission lines of length ZUL are attached to ports 1 and 2 in the Serenade model. Optimization is done by starting with the optimum filter parameters given in Fig. 6 and performing 1500 iterations with the random optimizer. The solution was found without any manual interaction.It took 35 minutes on a PC with a clock speed of 400 MHz. Figs. 15 through 17 show curve fitting results. Notice, in Fig. 15, that there is still a few hundredths of a dB difference between the HFSS results and the best fit in Serenade. This indicates that thisdesign method is accurate to a few hundredths of a dB.Fig. 13 Serenade setup used for curve fitting: top level schematicFig. 14 Serenade setup used for curve fitting: Model definition as sub circuitFig. 15 Result of curve fitting, magnitudeFig. 16 Result of curve fitting, phaseFig. 17 Results of curve fitting, complex S11 Blue and green lines are S_11 and S_22 from HFSS, which have the same magnitude but slightly differentphases; red line is the best fit.The result of the curve fitting procedure is as follows: we have built a filter with Resonant frequency of the outermost resonators f R1= 400.058 MHzResonant frequency of the inner resonators f R2=399.926 MHzLoaded Q Q L=30.368Coupling coefficients K12=0.02825 , K23=0.02173 , K34=0.02068Notice that the largest discrepancies occur in K12 and Q L. Apparently, the calibration project that determines the coupling coefficient by simulating two identical resonators is not quite representative of the two outermost pairs of resonators, where one resonator is coupled through an antenna to the source or the load. Also, the calibration project that determines the loaded Q by simulating one resonator-antenna combination is not perfectly representative of the real situation where this resonator is coupled to a neighboring one.Nevertheless, the calibration projects tell us how much correction is needed to achieve the desired characteristic. For example, noticing that Q L is too low by a certain amount, we will aim for a Q L that is higher by this amount the second time. Caution is needed when adjusting the antenna distance, since that also changes f R1. We have to change antenna distance and resonator length simultaneously, and aim for the correct Q Land f R1.Keeping this in mind, with the aid of the calibration projects we find that the dimensions of the filter are to beLength of the two outermost resonators = 113.44 mmLength of the five inner resonators = 114.684 mmAntenna distance = 1.928 mmDistances between resonators are 25.286 mm , 28.3 mm , 28.78 mm Hence, the dimensions that undergo the largest changes are the antenna distance and the distance between the first and second resonator.6 Corrected Filter Design in HFSSThe corrected filter was modeled and simulated in Ansoft HFSS. The resulting characteristic and the corresponding Smith chart are shown in Figs. 18a and 18b. Note that the ripple, which was 0.3 dB in the initial design, is better than 0.13 dB now. The target is 0.1 dB.Fig. 18a S21 results in HFSS for the corrected designFig. 18b Smith chart in HFSS for the corrected designIn order to obtain this result, the mesh was refined adaptively until it had 180,000 tetrahedra. With a mesh that size, the calculation of each frequency point required 1.28 GB of RAM and 9.5 minutes real time on a 1.2 GHz PC with one processor. Seventeen frequency points were needed for an interpolating frequency sweep, bringing the total time needed for the sweep to two hours and forty minutes. An identical model with only 119,000 tetrahedra (see below) provided results within a few hundredths of a dB in the pass band and saved almost half the time.7 Additional Information from the 3D Field Solver7a Effects of Internal LossesAll simulations thus far have been performed with lossless filters. A simulation without loss results in computations with real numbers only, as opposed to computations with complex numbers. This reduces the RAM requirement and the CPU time significantly. Once the design has been finalized, however, one can easily change the material parameters and boundary conditions to go from perfectly-conducting metals to lossy metals like copper or silver. The software enables you to select materials from a database or specify the conductivity. A plot comparing a lossless and a silver filter is shown in Fig. 19. Notice that, due to the seven consecutive resonances, even with a very good conductor like silver the insertion loss will be between 0.5 and 1 dB.Fig. 19 Comparison lossless filter and silver-plated filterAlso note that the center frequency of the silver filter is slightly lower than the center frequency of the perfect filter. A careful inspection of the data shows that this shift is between 0.07 and 0.08 MHz. A model with just one resonator shows the same shift. Further investigation reveals that this shift is due to the imaginary part of the surface impedance of the silver. According to electromagnetic theory, the conductivity of the silver translates into an equivalent surface impedance, provided that the metal thickness is much larger than the skin depth. This surface impedance has a real and an imaginary part, which are both equal to √ (πfμ0μR/σ), where f is the frequency, μ0μR is the permeability of the material, and σ is the conductivity of the material. In the case of silver at 400 MHz the surface impedance is Z surface= 5(1+j) mΩ/square. A simulation in HFSS with Z surface = 5 mΩ/sq uare shows no frequency shift at all relative to the perfect conductor case, while a simulation with Z surface= 5j mΩ/square shows the same shift as in Fig. 19.Curve fitting with Serenade shows that replacing perfect conductors by silver in HFSS is equivalent to introducing an unloaded Q of 2,800 in each resonator in Serenade. According to filter theory, the introduction of an unloaded Q shifts the resonant frequency downward by f r/(2Q), which in this case equals 0.07 MHz. Hence, HFSS has predicted this frequency shift very accurately.In order to account for this shift, designers should first determine the magnitude of the shift with an HFSS simulation involving just one resonator. Then, they should design a perfectly lossless filter around a frequency that is higher by this amount. The center frequency of the filter with internal losses will thus come out just right.The computer requirements were as follows. These computations have been performed with a model with 119,000 tetrahedra. In the lossless case, this took 810 MB RAM, 207 MB disk, and 86 minutes real time on a PC with a clock speed of 1.2 GHz and one processor. In the lossy case, it took 1,332 MB RAM, 1,600 MB disk and 396 minutes real time. The large time difference is due to the change from a real to a complex solver and to the time needed for disk access. The disk access in this case is …spill logic‟, which is a deliberate process, performed under the software‟s control. It is not to be confused with the very inefficient …swapping‟ which is done by the operating system when a process is too large for the available RAM.7b Maximum Power-Handling CapabilityIt is important to know how much power the filter can handle. The maximum power handling capability can be obtained easily with the help of a field plot. Fig. 20 shows a close up of the fields around a resonator in the region where they are strongest.Fig. 20 Fields around a resonatorThe HFSS 3D Fields Post Processor tells us that, with 1 W input power, the electric field strength between the cylinder and the bucket is 105 kV/m. You can change the input power in the post processor (Data/Edit Sources). The filter would cease to operate when the fields are strong enough to cause arcing in the air. This phenomenon occurs at 3 MV/m, although, with a wide safety margin, 1 MV/m is commonly used as the maximum acceptable field strength. Therefore, the fields can be allowed to be 9.5 times as strong as they are now, which implies that the maximum power handling capability is 9.5×9.5 = 90 W.7c Mechanical TolerancesOnce the dimensions are known that provide a filter with the desired specifications, it is important to establish mechanical tolerances. With the HFSS model fully parameterized in Optimetrics, it is an easy task to explore the effects of smalldimensional changes on the filter characteristic. An example is shown in Fig. 21. There,the distance between two resonators was made 0.08 mm larger and 0.08 mm smaller. The original characteristic and the two modified ones are shown. In this case, a manufacturing inaccuracy of 0.08 mm in the distance between two resonators results in a change of up to 0.05 dB in the filter characteristic. This way, mechanical tolerances, depending on the accuracy requirements of the filter characteristic, can be specified.Fig. 21 Example of the effects of manufacturing tolerancesReferences[1] Daniel G. Swanson and Robert J. Wenzel, “Fast Analysis and Optimization of Combline Filters Using FEM”, presented at the IEEE MTT Soc iety 2001 International Microwave Symposium, May 2001.[2] Randall W. Rhea, “HF Filter Design and Computer Simulation”McGraw-Hill, Inc., 1995ISBN 0-07-052055-0Appendix A Derivation of the CircuitIn this appendix, the well known low-pass prototype method for filter designs is repeated. Only the necessary facts for the present example are given. For more details a standard book on filter designs should be used [A1]. The starting point of this method is the low-pass prototype as shown in Figs. A1 and A2. These filters are normalized to a cut-off angular frequency of 1 rad/s and a generator impedance of 1 Ohm. In the case of a Chebychev filter some care has to be taken regarding the order of the filter. For an odd number of elements the load impedance is also 1 Ohm. For an even number of elements, however, the load impedance depends on the order of the filter and the ripple. Therefore, the two cases are treated separately.g = 1g N-1g Ng 3g = 1 N+1Fig. A1Low-pass prototype for the case N=oddg = 1g Ng 3g N-1g = 1N+1Fig. A2Low-pass prototype for the case N=evenIn the past, the prototype values g i (i = 1 … N+1) were read from tables, but nowadays it is more convenient to use a filter design program. Chebychev filters aredefined by the filter order N and the in-band ripple. Closed-form expressions exist for the g-values. An example is given in Fig. A3. This MathCAD program is valid for even as well as odd order filters for any ripple value. Essentially the g-values are defined by a recursive relation. Only for the last value a special treatment for the even and odd order case is necessary. This is considered by an if –statement with the mod –function ascondition. Exact definitions of these functions are given in the MathCAD handbook [A3]. The response of this filter is shown in Fig. A4.N 6:=ripple 0.1:=eps 10ripple 101-:=K i ()4sin 2i 1-()⋅1-2N⋅π⋅⎡⎢⎣⎤⎥⎦sin 2i 1-()⋅1+2N⋅π⋅⎡⎢⎣⎤⎥⎦⋅sinh asinh 1eps ⎛ ⎝⎫⎪⎭N ⎛ ⎝⎫⎪⎪⎭⎛ ⎝⎫⎪⎪⎭2sin i 1-()π⋅N ⎡⎢⎣⎤⎦⎡⎢⎣⎤⎥⎦2+⋅:=G i ()if i 12sin π2N ⋅⎛⎝⎫⎪⎭sinh 1N asinh 1eps ⎛ ⎝⎫⎪⎭⋅⎛ ⎝⎫⎪⎭⋅,K i (),⎛⎝⎫⎪⎪⎪⎭:=g01:=gi i ()if i1G i (),G i ()gi i 1-(),⎛ ⎝⎫⎪⎭:=gnplus1if mod N 2,()01eps 1eps2++()2,1,⎡⎢⎢⎣⎤⎥⎥⎦:=g0nplus1i ()if i 0g0,gnplus1,():=g i ()if i N 1+()i 0()+g0nplus1i (),gi i (),[]:=j 0N 1+..:=g j ()=j =Fig. A3MathCAD program to derive the g-values for Chebychev filter responses. Example: N = 6, ripple = 0.1 dB.。
在HFSS中完成PCB与三维器件的联合仿真
HFSS 3D Layout的优势
• EDA操作风格 • 快速的网格生成 • 确保S参数的因果性和无源性 • 所有LAYOUT元素均为参数化模型 • 智能化端口设置 • 简洁的边界条件设置
HFSS 3D Layout在R17中的新功能
• 与HFSS项目的动态链接 • 三维器件布局 • LAYOUT显示优化
支持SIWAVE求解技术
• 完成大尺寸PCB的仿真 • Layout检查
• 线性网络协同仿真 • 网络分组 • 器件建模
三维器件布局演示
Agenda
• 3D Components • HFSS 3D LAYOUT • Layout Driven System Verification
Layout Driven System Verification
需要怎么样系统级电磁仿真？ 将三维实体器件，基于模型的器件与LAYOUT版图放在一起 各部分使用最合适的求解技术（HFSS, HFSS 3D LAYOUT或者SIWAVE） 基于自动化电路技术捕捉系统的整体效应
实施Layout Driven System Verification的步骤
Ansoft LLC 0.00
self ind S Plot 1
plane hole 4hfss
-2.50
-5.00
S Parameter in db
-7.50
-10.00
-12.50
Curve Info
dB(S(P1,P2)) self ind
dB(S(STRIPLINE_SYMMETRIC_PERFORATED_PLANE_A_0_T1,STRIPLINE_SYMMETRIC_PERFORATED_PLANE_A_0_T2)) Import1
HFSS在PCB共模滤波设计中的应用与研究
背景
• 常规的迷宫、导电胶条、导电泡棉、吸波材料、簧片等处理措施受 限于空间布局，需要储备PCB板级EMI抑制措施。
• DGS：defected-ground structur，缺陷地结构，应用在信号参 考地层，在高速信号参考地层按设计结构腐蚀挖槽，形成等效带阻 滤波器，达到抑制共模噪声的目的。
原理
感谢聆听
Байду номын сангаас
DGS技术对差模信号没影响，对共模信号抑制10dB+；
通过仿真分析介质厚度、DGS层铜厚、加工精度等因素的影响，评估实 际PCB制造过程中DGS效果差异，节省时间和成本；
HFSS操作界面简单，仿真效率高，仿真实测吻合良好，仿真可以指导 实际PCB设计。
参考文献
1S.-P. Gao, H. M. Lee, X.-K. Gao, P. Yu, C. Zhan, X. Feng, E.-X. Liu, and C. E. Png, “Common-mode filter using cavity-backed defected ground structure for multilayer pcb,” in 2016 Asia-Pacific Symposium on Electromagnetic Compatibility (APEMC 2016), 2016.
f0:中心频率， fc：3dB截止频率
仿真分析
HFSS建CHC型DGS，仿真分析共模滤波原理； 仿真建模，分析参考介质层厚度改变对DGS滤波效果影响； 仿真建模，分析DGS放置层铜厚改变对DGS滤波效果影响； 仿真建模，分析PCB腐蚀挖槽加工精度对DGS滤波效果影响； 仿真建模，分析PCB走线弯曲倒弧对DGS滤波效果影响； 仿真建模，分析多层PCB放置DGS滤波效果。
微波仿真论坛_应用Designer和HFSS对微波滤波器的协同仿真
7
些模型导入电路模块中 。在电路形式下 ,每个部分 被抽象成一个多端口器件 ,将这些多端口器件按逻 辑关系联结起来组成一个电路模型 ,这些电磁结构 模型被导入到电路模块中 ,它们仍保持其独立性 。 这样划分的理由是谐振杆处场的分布是对称的 ,切 面是理想电壁对称面 ,划分并不改变场的分布 ,对称 面的应用加快了求解速度 。图 4 为划分结构示意图 和电路端口连接模型 。
图 6 三种结构电路仿真结果
虽然都可得到近似的结果 ,但其中的原理有区 别 ,也说明了划分面选取的重要性 。
场模型中激励端口的模式数对应于电路模型中 的端口网络节点 ,为求解的准确 ,可增加设置模式 数 。对于波导和给定横截面的传输线 ,存在给定频 率下的一系列基本场模式 ,在波导中 ,场是这些模式 的线性组合 。仿真分析时不可能考虑所有的模式 , 而必须在一定的模式数处将场的级数求和式加以截 断 。由一个给定模式激励信号产生的场包含因结构 的不连续性而产生的高阶模式的反射 。这些高阶模 式被反射回激励端口或传输到另一端口 ,计算 S 参 数时必须考虑到这些模式 。所取模式数目的不同 , 求取精度就不同 。模式数太多 ,计算时间会增加 ,求 解精度不会显著提高 ,只需计算结果收敛即可 。
传统的等效电路法将复杂的场问题近似为一些简化 的级联公式可类似推导 。
的等效电路模型 ,其具有简单易行的特点 ,精度依赖
基于HFSS的带通滤波器设计论文
本科毕业设计（论文）题目基于HFSS的带通滤波器设计学院物理与电子工程学院年级08 专业电子信息工程班级 2 学号*********学生姓名刘建指导教师施阳职称讲师论文提交日期基于HFSS的带通滤波器设计摘要本文介绍了矩形杆交指型带通滤波器的原理和设计方法,根据交指滤波器的设计理论获得矩形杆的自电容和互电容,利用计算机辅助设计工具结合图表得到滤波器的初始尺寸。
给出了一个中心频率为1.5GHz,带宽为1GHz的矩形杆交指滤波器的设计过程,利用HFSS 软件仿真,提高了设计效率和精度,仿真结果和理论结果吻合良好,证明了设计方法的可行性。
关键词：HFSS软件带通滤波器交指型带通滤波器HFSS-based band-pass filter designAbstractThis paper gives the particular description of a theoretical analysis and practical design for rectangular -rod inter -digitalband-pass filter. First, the self - capacitance and mutual capacitance of the inter-digital band-pass filter is obtained in accordingwith the design theory of the inter-digital band-pass filter. Based on computer aided design, the parameters of filter are given. Filterwith pass-band centered at 1.5GHz and bandwidth is 1GHz, has been designed and simulated by HFSS-software, whichgreatly improves the efficiency and accuracy of the design. The simulation result shows good agreement with theoretical result, whichproves the method is valid.Key words:HFSS-software；band-pass filter;Cross-finger-type band-pass filter目录第一章绪论1.1HFSS软件简介HFSS是ANSOFT公司开发的一个基于物理原型的EDA设计软件.使用HFSS建立结构模型进行3D全波场分析,可以计算.①基本电磁场数值解和开边界问题,近远场辐射问题;②端口特征阻抗和传输常数;③S参数和相应端口阻抗的归一化S参数;④结构的本征模或谐振解.依靠其对电磁场精确分析的性能,使用户能够方便快速地建立产品虚拟样机,以便在物理样机制造之前,准确有效地把握产品特性,被广泛应用于射频和微波器件、天线和馈源、高速IC芯片等产品设计中.HFSS有本征模解( Eigenmode Solution)和激励解(Driven Solution)两种求解方式.选择Eigenmode Solution 用于计算某一结构的谐振频率以谐振频率点的场值和腔的空载Q0值.选择Driven Solution用于计算无源高频结构的S参数和特性端口阻抗、传播常数等。
射频ADS微波HFSS相关 射频实验三 射频滤波器
实验三射频滤波器实验一实验目的1．掌握射频低通、带通滤波器的工作原理2．学习使用ADS软件进行滤波器的设计、优化和仿真3．学会使用AV3620矢量网络分析仪测试滤波器的幅频特性二实验原理1 低通滤波器集总元件低通原型滤波器是设计微波滤波器的基础。
一般低通原型滤波器的两种可行结构如图3-1所示，它是个LC梯型网络，两端各接纯电阻负载，（a）与（b）两电路互为对偶，即串联电感与并联电容存在对换关系。
图3-1 低通原型滤波器的电路低通原型的频率响应通常有最平坦响应和等波纹响应两种。
最平坦型滤波器的衰减曲线中没有任何波纹，所以称为最大平滑滤波器，也称巴特沃斯滤波器。
其衰减函数为()2210lg 1n A L =+εΩ （3-1） 其中归一化频率'1ω'ωΩ=。
等波纹型滤波器的频率响应在通带内有规律性的起伏，且幅度相等，故称为等波纹型，也称为切比雪夫响应。
其衰减函数为()2210lg 1A n L T ⎡⎤=+εΩ⎣⎦ （3-2）与巴特沃斯低通原型相比较，对于给定的通带衰减和滤波器节数，切比雪夫低通原型的阻带衰减斜率陡峭得多。
2 带通滤波器发卡式滤波器是半波长耦合微带滤波器的一种变形结构，是把半波长耦合谐振器折合成“U ”字形构成的。
发卡式滤波器是由若干个发卡式谐振器并排排列组合而成，这些谐振器之间主要是通过其边缘区域的电磁场相互交叉耦合的。
因此，这部分区域决定了发卡式滤波器之间的耦合特性和耦合强度。
在每个谐振器两臂的开放端，电场强度分布达到最大；而在其两臂的中间部分，磁场强度分布达到最大。
如图3-2所示，根据谐振器间的相对位置，发卡式谐振器可以分为四种基本耦合结构：电耦合、磁耦合、第一及第二类混合耦合。
图中，a 为谐振器臂长，b 为臂间距，w 为线宽，s 为两谐振器间距，d 为两谐振器偏移距离。
图3-2 微带型发卡式谐振器的4类基本耦合结构对于相同的微带线结构，如果两个谐振器的s 和d 减小，其耦合性能必定增强。
基于HFSS的滤波器设计流程
基于HFSS的滤波器设计流程HFSS（High Frequency Structure Simulator）是一种强大的电磁场模拟软件，可用于设计和优化各种微波和射频滤波器。
下面是基于HFSS 的滤波器设计流程，包括滤波器的初步设计、模型的创建和分析、参数优化以及最后的仿真验证。
1.滤波器的初步设计：首先确定所需滤波器的类型和规格，如低通滤波器、带通滤波器或阻带滤波器等。
根据滤波器的频带宽度、中心频率、通带损耗和阻带衰减等要求，初步选择滤波器的结构和拓扑。
2.模型的创建和分析：在HFSS中创建滤波器的几何模型。
可以使用HFSS自带的CAD工具或第三方工具创建模型，并导入到HFSS中。
确保模型的几何形状和尺寸与设计要求相符。
之后，通过HFSS进行射频电磁场模拟分析。
设置合适的频率范围，并给出合适的激励条件。
根据模型的几何形状和材料特性，计算出滤波器的S参数、功率传输和电场分布等。
3.参数优化：根据分析结果，评估滤波器的性能是否满足设计要求。
如果结果不满足要求，需要对设计参数进行优化。
通过调整滤波器的几何形状、模型的材料特性或其他设计参数，再次进行HFSS模拟。
通过反复优化，逐步改善滤波器的性能。
可以使用HFSS自带的优化工具，如参数扫描、自动优化或遗传算法等，来寻找最佳的设计参数组合。
4.仿真验证：在完成参数优化后，对滤波器进行最后的仿真验证。
使用优化后的设计参数，进行HFSS模拟分析。
通过分析结果，检查滤波器是否满足设计要求，并评估其性能。
如果滤波器性能仍然不满足要求，可以进一步优化设计参数，或者重新考虑滤波器的拓扑结构。
5.后处理和导出：在完成仿真验证后，可以进行一些后处理操作，如绘制频率响应曲线、电场分布图或功率传输图等。
这些后处理结果对于滤波器的性能评估和进一步优化非常有帮助。
最后，可以将滤波器的设计参数导出，用于后续的原理图设计和实际制造。
可以导出滤波器的尺寸数据、材料特性和优化参数等。
一种PCB天线仿真工具HFSS简介
一种PCB天线仿真工具HFSS简介一种PCB天线仿真工具HFSS简介引言随着无线射频技术和电子电路技术的发展，射频模块的体积变的越来越小，高精密度，高性能的射频电路设计和高发射增益天线越来越收到行业内的重视。
由此，一种可靠的功能强大的天线仿真软件应运而生——HFSS天线仿真软件。
通过设计2.4G天线为例子，简单了解到HFSS软件设计天线的整个过程。
1、估算天线长度①已知工作频率（2.4~2.4835Ghz）,中心频率取2.45Ghz②已知PCB板信息，分别包括介质材料是FR4,Er = 4.4、板厚1mm、天线走线宽1.6mm、PCB板尺寸65*40mm、参考地大小40*40mm。
由①②得到天线总长度= 2.4Ghz时1/4自由空间波长和1/4个FR4介质波长的中间值也就是[ (3 * 10^8) / (2.45 * 10^9) / 4 +122 / (√4.4) / 4 ] / 2 =22.7mm由于是倒L天线，所以其中垂直长度8mm，水平长度14.7mm2、创建参数化模型a. 打开软件新建一个HFSS工程，并且命名为ILA，插入HFSSDesign，设置仿真方式DrivenTerminal，工程单位为mm。
如下图1。
图1b.定义各种设计变量的名称和对应的参考值如下图2图2c.重复b操作设置另外一些需要设置的天线信息变量。
得到图3。
图33、设置扫描条件在设置HFSS扫描条件之前，我们一般是先要设置天线的辐射端口，辐射端口默认阻抗为50欧姆（国际标准），在设置好端口之后就要设置仿真的辐射边界，辐射边界取1/4工作波长。
然后就可以设置其扫描条件，这个天线的中心频点是2.45G,为了节约仿真时间扫描的起始段设为2Ghz到3Ghz，扫描间隔为0.01Ghz。
设置完所有量就得到下图4了。
图44、分析结果，优化设计我们进行单一长度的参数扫描分析。
得到图5，显然由图5可以看出我们所设置的天线长度最佳的工作频率是在2.65Ghz左右，这并不是我们想要的。
hfss波端口尺寸共面波导
hfss波端口尺寸共面波导HFSS（高频结构模拟器）是一款广泛应用于射频和微波领域的电磁仿真软件，它具有强大的计算和分析能力，可以帮助工程师设计和优化高频器件。
其中的波端口尺寸共面波导是一种重要的技术，在微波传输中扮演着重要的角色。
接下来，我们将详细介绍HFSS波端口尺寸共面波导的特点和应用。
首先，让我们了解一下什么是波端口尺寸共面波导。
这是一种采用微带线或共面波导作为传输介质的器件，其波导和其它部分共面排列，从而实现高频信号的传输和耦合。
相比于常规的波导结构，波端口尺寸共面波导具有体积小、制造简单和可靠性高的优点，在高频器件和系统设计中得到了广泛应用。
波端口尺寸共面波导在射频和微波领域有着广泛的应用。
首先，它可以用于设计和优化天线结构。
通过在HFSS中建立天线模型并选择适当的波端口尺寸共面波导传输线，可以实现天线与传输线之间的低损耗、高效率的信号耦合。
其次，它还常用于微波滤波器的设计中。
通过在HFSS中建立滤波器模型并选择合适的波端口尺寸共面波导，可以实现滤波器的高性能和小尺寸化。
在使用HFSS进行波端口尺寸共面波导设计时，需要注意一些关键因素。
首先，波导的宽度、长度和高度等尺寸参数需要根据具体应用需求进行合理选择。
其次，波导的材料特性也要考虑进去，例如介电常数、导电率等。
此外，在优化波导性能时，还需要考虑到波导的损耗、带宽和驻波比等指标，以及其它相关因素。
总之，HFSS波端口尺寸共面波导是一种重要而实用的技术，在射频和微波领域具有广泛的应用。
通过合理设计和优化，可以实现高效率、低损耗的信号传输和耦合。
工程师们可以利用HFSS进行仿真和优化，以帮助解决高频器件和系统设计中的问题，并取得更好的性能和效果。
同时，持续不断地探索和创新，将为射频和微波技术的发展带来更多的突破和进步。
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
背景
• 结构件缝隙屏效随频率升高而下降
背景
• 常规的迷宫、导电胶条、导电泡棉、吸波材料、簧片等处理措施受 限于空间布局，需要储备PCB板级EMI抑制措施。
小结
DGS技术对差模信号没影响，对共模信号抑制10dB+； 通过仿真分析介质厚度、DGS层铜厚、加工精度等因素的影响，评估实 际PCB制造过程中DGS效果差异，节省时间和成本；
HFSS操作界面简单，仿真效率高，仿真实测吻合良好，仿真可以指导 实际PCB设计。
参考文献
[1] S.-P. Gao, H. M. Lee, X.-K. Gao, P. Yu, C. Zhan, X. Feng, E.-X. Liu, and C. E. Png, “Common-mode filter using cavity-backed defected ground structure for multilayer pcb,” in 2016 Asia-Pacific Symposium on Electromagnetic Compatibility (APEMC 2016), 2016. [2] X.-K. Gao, H. M. Lee, S.-P. Gao, E.-X. Liu, and C. E. Png, “A compact common-mode noise suppression filter for high speed differential signals using defected ground structure,” in 2015 Asia-Pacific Symposium on Electromagnetic Compatibility (APEMC 2015), 2015, pp. 685–688.
仿真实测分析
测试平台介绍；
仿真实测分析_差分信号；
仿真实测分析_单端信号。
测试平台
利用TRL校准方法，校除SMA连接头和非理想差分线走线影响； 利用四端口网分测试S参数，提取差模信号和共模信号S参数； 仿真实测对比分析DGS对差模和共模影响。
仿真实测分析_差分走线
仿真实测分析_单端走线
感谢聆听
参考地层铜厚影响
改变高速参考地层铜皮厚度，共模抑制变化小。
槽加工精度影响
考虑加工腐蚀公差，对最小尺寸做容差分析，发现影响不大。
高速线倒弧影响
考虑表层走线倒弧、弯曲，仿真发现影响不大。
多层PCB应用问题分析
实际多层PCB，DGS放置不能影响布局布线； DGS下方地不挖穿情况下，共模滤波带宽变窄。
仿真建模，分析DGS放置层铜厚改变对DGS滤波效果影响； 仿真建模，分析PCB腐蚀挖槽加工精度对DGS滤波效果影响； 仿真建模，分析PCB走线弯曲倒弧对DGS滤波效果影响； 仿真建模，分析多层PCB放置DGS滤波效果。
电流分布
参考介质厚度影响
改变高速参考介质厚度，调整差分线宽线距，共模抑制变化小。
HFSS在PCB共模滤波设计中 的应用与研究
• 占存辉/EMC工程师 • HUAWEI
目录
背景介绍 摘要 原理
仿真分析
仿真实测分析 小结 参考文献
摘要
• 本文针对PCB高速走线引入的共模噪声抑制问题进行了深入研究，
给出了DGS（缺陷地滤波器）理论分析，并利用仿真软件HFSS设
• DGS：defected-ground structur，缺陷地结构，应用在信号参
考地层，在高速信号参考地层按设计结构腐蚀挖槽，形成等效带阻
滤波器，达到抑制共模噪声的目的。
原理
f0:中心频率， fc：3dB截止频率
仿真分析
HFSS建CHC型DGS，仿真分析共模滤波原理；
仿真建模，分析参考介质层厚度改变对DGS滤波效果影响；