romão kowaltschuk 1,2 wilson arnaldo artuzi jr. 1 oscar da costa gouveia filho 1
DESCRIPTION
Design of Integrated Inductors through Selection from a Database Obtained by Electromagnetic Simulation and Neural Networks. Design of Integrated Inductors Through Selection from a Database Created Using Electromagnetic Simulation and Neural Networks. Romão Kowaltschuk 1,2 - PowerPoint PPT PresentationTRANSCRIPT
Romão Kowaltschuk1,2
Wilson Arnaldo Artuzi Jr.1
Oscar da Costa Gouveia Filho1
1 - UFPR – Universidade Federal do Paraná
2 - Copel – Companhia Paranaense de Energia
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
September, 2003
Design of Integrated Inductors Through Selection from a Database Created Using Electromagnetic Simulation and Neural
Networks
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
1 INTRODUCTION
2 INDUCTORS DESIGN
3 ELECTROMAGNETIC SIMULATION
4 RESULTS OF ELECTROMAGNETIC SIMULATION
5 NEURAL NETWORKS
6 CONCLUSIONS
OUTLINE
- Objective: Transceptor complete integration.- A problem:Passive devices (inductors) integration.
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Technology Advantages Negative Points
GaAs
- Speed- Highly resistive substrate- Passive component construction is not difficult
- Low density of integration- High costBipolar
- Speed- High Fan-out avaiability
- Low density of integration
CMOS- Low power- High density of integration- Low cost
Bipolar/CMOS
- Conductive substrate
-Isn’t avaiable in standard manufacturing plants
- Joins advantages of bipolar/CMOS
INTRODUCTION
INDUCTORS DESIGN
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Inductors
- Devices with no standard design
Project Techniques
- Empirical formulations
- Analythic formulation derived from electromagnetic theory
- Electromagnetic simulation (finite elements and numerical methods)
Design Variables
- Too many variables to be chosen in design
Cox = oxide capacitanceRSi = silicon conductivityCSi = high frequency capacitive effects that occur in the semicondutor
Lumped Parameters Considering the Substrate
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Basic Electrical Model of the Inductor
CS = capacitance of overlaying metal layersRs = conductivity of spiral metalLs = high frequency inductive effects of that occur in the spiral metal
Lumped Parameters Considering the Spiral
Belief: the electromagnetic simulation gives a good evaluation of results, concerning the variation of reactance with frequency, but it demands a lot of effort!
Solution: to do electromagnetic simulation automatically!
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Electromagnetic Simulation - An Alternative Solution
An inductor base case editor program for batch simulation
An electromagnetic specific purpose simulator (ASITIC)
capable of providing continous outputs for simulation cases
of thousands of devices.
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
A program to classify results, due to the huge amount of
data!
(a simple software written in VB6)
Automatization of Electromagnetic Simulation
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Geometric Specification of Inductors Results of Electromagnetic Simulation
Typical Device Specified in Database
Database Description
Results of Electromagnetic Simulation
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Database Variable Search Criteria
- Normalized inductive reactance between input and output terminals
5,0 nH<=jX/jw<= 5,2nH
- Inductor’s spiral circumscript radius- Resonant Frequency
Radius < 200 m
f > 3,5 GHz
Partial Vision of the Answer to the Requested Question
Spiral Ident.Number
Radius(m)
Operational freq.(MHz)
Normal. Induc.Reactance(nH)
ResonantFrequency(GHz)
931....9311048.....1048
175....175150.....150
200....1600200.....1400
5,094....5,1325,090.....5,104
6,922....8,7967,088.....6,580
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Design Example
A possible answer: evaluating some values of the electrical
parameters database using neural
networks trained using a smaller set of
data obtained by eletromagnetic
simulation.
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Question: how could it be possible to decrease the
time spent in eletromagnetic simulation?
Creating the Inductor’s Electrical Database Using Neural Networks
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
Results Obtained Using Neural Networks
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
The proposed design method enables evaluation of inductive
reactances for a wide range of frequencies and can justify the
development of the sofware tools and the avaiability of computer
resources necessary to realize it.
CONCLUSIONS
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks
The evaluation of normalized inductive reactances, through
electromagnetic simulation is the only theoretical model that
shows the designer a trustable performance of inductors, as
frequency varies in a wide range.
The alternative design method of creating some of the values
necessary to complete a searchable database employing neural
networks has achieved reasonable results just for evaluating
reactances of big and medium size inductors (outer sides >= 100
µm).
For smaller devices, the performance of neural networks is not
acceptable. The values obtained are worth just for indicating a
range of values.
CONCLUSIONS
Design of Integrated Inductors through Selection froma Database Obtained by Electromagnetic Simulation andNeural Networks