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Scalable macromodelling methodology for the efficient design of microwave filters

Matthias Caenepeel, Krishnan Chemmangat Manakkal Cheriya, Francesco Ferranti, Yves Rolain, Tom Dhaene UGent and Luc Knockaert UGent (2016) IET MICROWAVES ANTENNAS & PROPAGATION. 10(5). p.579-586
abstract
The complexity of the design of microwave filters increases steadily over the years. General design techniques available in literature yield relatively good initial designs, but electromagnetic (EM) optimisation is often needed to meet the specifications. Although interesting optimisation strategies exist, they depend on computationally expensive EM simulations. This makes the optimisation process time consuming. Moreover, brute force optimisation does not provide physical insights into the design and it is only applicable to one set of specifications. If the specifications change, the design and optimisation process must be redone. The authors propose a scalable macromodel-based design approach to overcome this. Scalable macromodels can be generated in an automated way. So far the inclusion of scalable macromodels in the design cycle of microwave filters has not been studied. In this study, it is shown that scalable macromodels can be included in the design cycle of microwave filters and re-used in multiple design scenarios at low computational cost. Guidelines to properly generate and use scalable macromodels in a filter design context are given. The approach is illustrated on a state-of-the-art microstrip dual-band bandpass filter with closely spaced pass bands and a complex geometrical structure. The results confirm that scalable macromodels are proper design tools and a valuable alternative to a computationally expensive EM simulator-based design flow.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
ELECTROMAGNETIC OPTIMIZATION, CAD-MODEL CONSTRUCTION, CAUCHY METHOD, RESPONSES, IMPLEMENTATION, FRAMEWORK, SYSTEMS, IBCN
journal title
IET MICROWAVES ANTENNAS & PROPAGATION
volume
10
issue
5
pages
579 - 586
Web of Science type
Article
Web of Science id
000373885700015
JCR category
ENGINEERING, ELECTRICAL & ELECTRONIC
JCR impact factor
1.187 (2016)
JCR rank
172/260 (2016)
JCR quartile
3 (2016)
ISSN
1751-8725
DOI
10.1049/iet-map.2014.0678
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
7240510
handle
http://hdl.handle.net/1854/LU-7240510
date created
2016-06-01 10:59:17
date last changed
2016-12-19 15:42:32
@article{7240510,
  abstract     = {The complexity of the design of microwave filters increases steadily over the years. General design techniques available in literature yield relatively good initial designs, but electromagnetic (EM) optimisation is often needed to meet the specifications. Although interesting optimisation strategies exist, they depend on computationally expensive EM simulations. This makes the optimisation process time consuming. Moreover, brute force optimisation does not provide physical insights into the design and it is only applicable to one set of specifications. If the specifications change, the design and optimisation process must be redone. The authors propose a scalable macromodel-based design approach to overcome this. Scalable macromodels can be generated in an automated way. So far the inclusion of scalable macromodels in the design cycle of microwave filters has not been studied. In this study, it is shown that scalable macromodels can be included in the design cycle of microwave filters and re-used in multiple design scenarios at low computational cost. Guidelines to properly generate and use scalable macromodels in a filter design context are given. The approach is illustrated on a state-of-the-art microstrip dual-band bandpass filter with closely spaced pass bands and a complex geometrical structure. The results confirm that scalable macromodels are proper design tools and a valuable alternative to a computationally expensive EM simulator-based design flow.},
  author       = {Caenepeel, Matthias and Chemmangat Manakkal Cheriya, Krishnan and Ferranti, Francesco and Rolain, Yves and Dhaene, Tom and Knockaert, Luc},
  issn         = {1751-8725},
  journal      = {IET MICROWAVES ANTENNAS \& PROPAGATION},
  keyword      = {ELECTROMAGNETIC OPTIMIZATION,CAD-MODEL CONSTRUCTION,CAUCHY METHOD,RESPONSES,IMPLEMENTATION,FRAMEWORK,SYSTEMS,IBCN},
  language     = {eng},
  number       = {5},
  pages        = {579--586},
  title        = {Scalable macromodelling methodology for the efficient design of microwave filters},
  url          = {http://dx.doi.org/10.1049/iet-map.2014.0678},
  volume       = {10},
  year         = {2016},
}

Chicago
Caenepeel, Matthias, Krishnan Chemmangat Manakkal Cheriya, Francesco Ferranti, Yves Rolain, Tom Dhaene, and Luc Knockaert. 2016. “Scalable Macromodelling Methodology for the Efficient Design of Microwave Filters.” Iet Microwaves Antennas & Propagation 10 (5): 579–586.
APA
Caenepeel, M., Chemmangat Manakkal Cheriya, K., Ferranti, F., Rolain, Y., Dhaene, T., & Knockaert, L. (2016). Scalable macromodelling methodology for the efficient design of microwave filters. IET MICROWAVES ANTENNAS & PROPAGATION, 10(5), 579–586.
Vancouver
1.
Caenepeel M, Chemmangat Manakkal Cheriya K, Ferranti F, Rolain Y, Dhaene T, Knockaert L. Scalable macromodelling methodology for the efficient design of microwave filters. IET MICROWAVES ANTENNAS & PROPAGATION. 2016;10(5):579–86.
MLA
Caenepeel, Matthias, Krishnan Chemmangat Manakkal Cheriya, Francesco Ferranti, et al. “Scalable Macromodelling Methodology for the Efficient Design of Microwave Filters.” IET MICROWAVES ANTENNAS & PROPAGATION 10.5 (2016): 579–586. Print.