Transcript Document
EEE 498/598
Overview of Electrical
Engineering
Lecture 1:
Introduction to Electrical
Engineering
1
Lecture 1 Objectives
To provide an overview of packaging.
To review the electrical functions of a package.
To understand the foundations of electrical
engineering.
To become aware of the topics that will be
covered in this class.
To define the coordinate systems that will be
used in this class.
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Lecture 1
Overview of Packaging
~ .040”
~ .012“
Silicon Die
Package
Motherboard
Courtesy of Intel Corp.
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Lecture 1
Overview of Packaging
IHS
FCBGA
Interposer
Caps
Interposer
LSC
Pins
Die
C4 Balls
Microvias
Interposer
FCBGA
PTH Vias
FCBGA
BGA Balls
Die
Interposer
Vias
Interposer
DSC
Pins
Courtesy of Intel Corp.
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Lecture 1
Overview of Packaging
“Packaging engineers today must solve
complex, coupled problems that require
fundamental understanding of electrical,
thermal, mechanical, material science,
and manufacturing principles.”
Dr.
Nasser Grayeli, Intel Corporation
This course focuses on preparing students
to understand the electrical principles.
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Lecture 1
Electrical Functions of the Package
Power Delivery
Signal Input/Output
Supply a clean power and reference voltage to active devices
on the die.
Transmit signals from the die to the motherboard faithfully
and in minimum time.
EMI/EMC
Minimize radiation of electromagnetic energy into the
environment, and the impact of ambient electromagnetic
energy on circuit performance.
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Lecture 1
Foundations of Electrical
Engineering
Electrophysics.
80 % of this course
Information
(Communications) Theory.
Digital Logic.
20 % of this course
Not covered in detail in this class
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Lecture 1
Foundations of Electrical
Engineering
Electrophysics:
Fundamental
theories of physics and
important special cases.
Phenomenological/behavioral models for
situations where the rigorous physical theories
are too difficult to apply.
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Lecture 1
Hypothesis, Model, and Theory
A hypothesis is an idea or suggestion that has been put
forward to explain a set of observations. It may be
expressed in terms of a mathematical model. The
model makes a number of predictions that can be
tested in experiments. After many tests have been
made, if the model can be refined to correctly describe
the outcome of all experiments, it begins to have a
greater status than a mere suggestion.
A theory is a well-tested and well-established
understanding of an underlying mechanism or process.
The material in this slide has been adapted from material at
http://www2.slac.stanford.edu/vvc/theory/modeltheory.html.
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Lecture 1
Hypothesis, Model, and Theory
Maxwell’s equations are ‘just a theory’ and yet my cell
phone works!
At one time, a theory would have been referred to as a
‘law’.
Newton’s laws
Boyle’s law
But remember no theory is a complete description of
all reality; all theories are incomplete.
Electrical engineers make use of a number of theories
– some of which are special cases of others.
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Lecture 1
Four Fundamental Forces of Physics
Gravitational Force
Electromagnetic Force
Associated particle is photon
1042 times stronger than gravity
Force can be attractive or repulsive
Varies inversely as the square of the distance
Strong Interaction
Associated particle is graviton (hypothesized)
Always attractive
Varies inversely as the square of the distance
Associated particle is gluon
About 100X stronger than electromagnetic force but only acts over distances
the size of an atomic nucleus
Responsible for holding the protons and neutrons together
Weak Interaction
Associated particles are the weak gauge bosons (Z and W particles)
Acts only over distances the size of an atomic nucleus
Responsible for certain types of radioactive decay
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Lecture 1
The Standard Model
Physicists call the theoretical framework that describes
the interactions between elementary building blocks
(quarks and leptons) and the force carriers (bosons) the
Standard Model.
Most of the standard model is a theory; some of it is
still hypothesis.
Physicists use the Standard Model to explain and
calculate a vast variety of particle interactions and
quantum phenomena. High-precision experiments have
repeatedly verified subtle effects predicted by the
Standard Model.
The material in this slide and in the following two slides has been adapted from
material from www.fnal.gov (Fermilab).
Lecture 1
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The Standard Model
The biggest success of the Standard Model is
the unification of the electromagnetic and the
weak forces into the so-called electroweak
force.
Many physicists think it is possible to eventually
describe all forces with a Grand Unified Theory
or a so-called Theory of Everything (ToE).
M-theory (a generalization of superstring theory) is
the current embodiment of the ToE.
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Lecture 1
Philosophical Implications of a ToE
Reductionist point-of-view: everything from the big
bang to human emotions can be obtained from the
ToE given enough computational power.
Another point of view: new types of fundamental laws
arise in complex systems that cannot be derived from
the ToE.
Practical point of view: any ToE could never be
successfully applied to complex systems, and so it is
irrelevant whether or not the laws of complex systems
can be derived from the ToE.
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Lecture 1
Religion/Faith/Metaphysics v.
Science
Science attempts to explain the processes
by which the universe functions (i.e. the
“how”).
Religion attempts to explain why the
universe exists and to impart meaning to its
existence (i.e., the “why”).
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Lecture 1
Religion/Faith/Metaphysics v.
Science
Science is absolutely neutral on the issue of whether
“God” exists or not.
Consider the following: people of many different faiths or no
faith at all can work together to design complex systems such
as a packaged integrated circuit.
Millions of devoutly religious people accept scientific
theories as valid explanations for natural processes.
Those who do not should imagine what life was like for
the average human before modern scientific advances
in medicine, engineering, etc.
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Lecture 1
Engineering
With the exception of nuclear engineering,
the engineering disciplines (e.g.,
mechanical, aerospace, civil, etc.) deal with
phenomena that involve the forces of
gravity and electromagnetism.
Much of electrical engineering involves
understanding phenomena that result from
the force of electromagnetism.
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Lecture 1
Hierarchy of Physics Theories Involved
in the Study of Electrical Engineering
Quantum electrodynamics
Quantum
mechanics
Schrödinger
Classical
equation
electromagnetics
Electrostatics
Magnetostatics
Circuit
theory
Geometric optics
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Lecture 1
Information Theory
Originally developed by Claude Shannon of Bell
Labs in the 1940s.
Information is defined as a symbol that is
uncertain at the receiver.
The fundamental quantity in information theory
is channel capacity – the maximum rate that
information can be exchanged between a
transmitter and a receiver.
The material in this slide and the next has been adapted from material from
www.lucent.com/minds/infotheory.
Lecture 1
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Information Theory
Defines relationships between elements of
a communications system. For example,
Power
at the signal source
Bandwidth of the system
Noise
Interference
Mathematically describes the principals of
data compression.
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Lecture 1
Exercise: What is Information?
Message with redunancy:
“Many
students are likely to fail that exam.”
Message coded with less redundancy:
“Mny
stdnts are lkly to fail tht exm.”
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Lecture 1
Digital Logic
Digital logic signals are really analog
signals, and digital circuits are ultimately
designed using circuit theory.
However, in many situations the function
of a digital circuit is more easily
synthesized using the principles of digital
logic.
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Lecture 1
Digital Logic
Based on logic gates, truth tables, and
combinational and sequential logic circuit
design
Uses Boolean algebra and Karnaugh maps
to develop minimized logic circuits.
Not explicitly addressed in this class.
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Lecture 1
EE Subdisciplines
Power Systems
Electromagnetics
Solid State
Communication/Signal Processing
Controls
Digital Design
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Lecture 1
Power Systems
Generation of electrical energy
Storage of electrical energy
Distribution of electrical energy
Rotating machinery-generators, motors
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Lecture 1
Electromagnetics
Propagation of electromagnetic energy
Antennas
Very high frequency signals
Fiber optics
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Lecture 1
Solid State
Devices
Transistors
Diodes (LED’s, Laser diodes)
Photodetectors
Miniaturization of electrical devices
Integration of many devices on a single
chip
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Lecture 1
Communications/Signal Proc.
Transmission of information electrically
and optically
Modification of signals
enhancement
compression
noise reduction
filtering
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Lecture 1
Controls
Changing system inputs to obtain desired
outputs
Feedback
Stability
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Lecture 1
Digital Design
Digital (ones and zeros) signals and hardware
Computer architectures
Embedded computer systems
Microprocessors
Microcontrollers
DSP chips
Programmable logic devices (PLDs)
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Lecture 1
Case Study: C/Ku Band Earthstation Antennas
Simulsat
Parabolic
Multiple horn feeds
Horn feed
ATCi Corporate Headquarters
450 North McKemy
Chandler, AZ 85226 USA
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Lecture 1
Case Study: C/Ku Band Earthstation Antennas
Incoming plane wave is
focused by reflector at
location of horn feed.
Geometric
Optics
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Lecture 1
Case Study: C/Ku Band Earthstation Antennas
Feed horn is
designed so that it
will illuminate the
reflector in such a
way as to maximize
the aperture
efficiency.
Maxwell’s
equations
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Lecture 1
Case Study: C/Ku Band Earthstation Antennas
Feed horn needs to
be able to receive
orthogonal linear
polarizations (V-pol
and H-pol) and
maintain adequate
isolation between the
two channels.
V-pol
H-pol
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Lecture 1
Case Study: C/Ku Band Earthstation Antennas
A planar orthomode
transducer (OMT) is
used to achieve good
isolation between
orthogonal linear
polarizations.
Maxwell’s Equations
(“Full-Wave
Solution”)
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Lecture 1
Case Study: C/Ku Band Earthstation Antennas
To LNB
Feed waveguide
(WR 229)
Maxwell’s
equations
Horn
Stripline circuit with OMT,
ratrace and WR229 transitions
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Lecture 1
Case Study: C/Ku Band Earthstation Antennas
Layout of the stripline trace layer
Single-ended probe
WR229
Transitions
Circuit
Theory
Differential-pair probes
Ratrace hybrid
50 ohm transmission line
Vias
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Lecture 1
Case Study: C/Ku Band Earthstation Antennas
The two linear
polarizations each
are fed to a LNB
(low noise block).
LNB
LNB
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Lecture 1
Case Study: C/Ku Band Earthstation Antennas
LNB:
LNA
Mixer
BPF
IF Output:
950-1750 MHz
(To Receiver)
Circuit
Theory,
Behavioral
Models,
Information
Theory
Local
Oscillator
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Lecture 1
Overall System Performance
Carrier-to-noise ratio (CNR)
Bit error rate (BER)
Maxwell’s Equations, Circuit
Theory, Behavioral Models,
Information Theory
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Lecture 1
SI (International System of) Units
Fundamental SI Units
Quantity
Unit
Abbreviation
length
meter
m
mass
kilogram
k
time
second
s
current
ampere
A
temperature
kelvin
K
luminous
intensity
candela
cd
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Lecture 1
Why Do We Need Coordinate
Systems?
The laws of electrophysics (like the laws of physics
in general) are independent of a particular
coordinate system.
However, application of these laws to obtain the
solution of a particular problem imposes the need
to use a suitable coordinate system.
It is the shape of the boundary of the problem that
determines the most suitable coordinate system to
use in its solution.
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Lecture 1
Orthogonal Right-Handed
Coordinate Systems
A coordinate system defines a set of three
reference directions at each and every point in space.
The origin of the coordinate system is the reference
point relative to which we locate every other point
in space.
A position vector defines the position of a point in
space relative to the origin.
These three reference directions are referred to as
coordinate directions, and are usually taken to be
mutually perpendicular (orthogonal).
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Lecture 1
Orthogonal Right-Handed
Coordinate Systems
Unit vectors along the coordinate directions
are referred to as base vectors.
In any of the orthogonal coordinate systems,
an arbitrary vector can be expressed in terms
of a superposition of the three base vectors.
Consider base vectors such that
Such a
aˆ1 aˆ 2 aˆ3
aˆ3
coordinate
aˆ 2 aˆ3 aˆ1
system is called
right-handed.
aˆ3 aˆ1 aˆ 2
aˆ1
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Lecture 1
Orthogonal Right-Handed
Coordinate Systems
Note that the base vectors can, in general,
point in different directions at different
points in space.
Obviously, if they are to serve as
references, then their directions must be
known a priori for each and every point in
space.
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Lecture 1
Coordinate Systems Used in
This Class
In this class, we shall solve problems
using three orthogonal right-handed
coordinate systems:
Cartesian x, y, z
, , z
spherical r , ,
cylindrical
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Lecture 1
Cartesian Coordinates
The point P(x1,y1,z1) is located as the
intersection of three mutually perpendicular
planes: x=x1, y=y1, z=z1.
The base vectors are aˆ x , aˆ y , aˆ z
The base vectors satisfy the following
relations: aˆ x aˆ y aˆ z
aˆ x
aˆ y aˆ z aˆ x
aˆ z aˆ x aˆ y
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aˆ z
aˆ y
Lecture 1
Cylindrical Coordinates
The point P(1,1,z1) is located as the
intersection of three mutually perpendicular
surfaces: =1 (a circular cylinder), =1 (a
half-plane containing the z-axis), z=z1 (a
plane).
The base vectors are aˆ , aˆ , aˆ z
aˆ is a unit vecto r in the direction of increasing
aˆ is a unit vecto r in the direction of increasing
aˆ z is a unit vecto r in the direction of increasing z
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Lecture 1
Cylindrical Coordinates
(Cont’d)
z
aˆ z aˆ
z1
P(1,1,z1)
1
aˆ
y
1
x
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Lecture 1
Cylindrical Coordinates
(Cont’d)
The base vectors satisfy the following
relations:
aˆ
aˆ aˆ aˆ z
aˆ aˆ z aˆ
aˆ z aˆ aˆ
aˆ z
aˆ
aˆ p aˆq pq ; p, q , , z
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Lecture 1
Spherical Coordinates
The point P(r1,1,1) is located as the
intersection of three mutually perpendicular
surfaces: r = r1 (a sphere), 1 (a cone),
and =1 (a half-plane containing the z-axis).
The base vectors are aˆ r , aˆ , aˆ
aˆ r is a unit vecto r in the direction of increasing r
aˆ is a unit vecto r in the direction of increasing
aˆ is a unit vecto r in the direction of increasing
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Lecture 1
Spherical Coordinates (Cont’d)
z
aˆ
P(r1,1,1)
aˆ r
1
r1
aˆ
y
1
x
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Lecture 1
Spherical Coordinates (Cont’d)
The base vectors satisfy the following
relations:
aˆ r
aˆ r aˆ aˆ
aˆ aˆ aˆ r
aˆ aˆ R aˆ
aˆ
aˆ p aˆq pq ; p, q r , ,
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Lecture 1
Spherical Coordinates (Cont’d)
0r
z
0
0 2
or
r
y
x
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Lecture 1
Position Vector
Position vector:
r aˆ x x aˆ y y aˆ z z
aˆ aˆ z z
aˆ r r
Arbitrary function of position:
f r
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Lecture 1