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APEC 2015
Optimal Design of Inductive Components
Based on Accurate Loss and Thermal Models
Dr. Jonas Mühlethaler
APEC 2015
Introduction
System Layer
(GeckoCIRCUITS)
Component Layer
(GeckoMAGNETICS)
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
2
APEC 2015
Introduction
GeckoMAGNETICS
How are magnetic components
modeled in GeckoMAGNETICS?
(Gecko-Simulations; www.gecko-simulations.com)
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
3
APEC 2015
Introduction
System Layer
Component Layer
Material Layer
www.ferroxcube.com
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
4
APEC 2015
Introduction
Application of Inductive Components (1) : Buck Converter
(DC Current + HF Ripple)
Schematic
Current / Flux Waveform
Modeling Difficulties
Solutions
-
-
-
Non-sinusoidal current / flux
waveform
Current / flux is DC biased
-
-
Mittwoch, 4. März 2015
Gecko-Simulations AG
FFT of current waveform for the
calculation of winding losses
Determine core loss energy for each
segment and for each corner point in the
piecewise-linear flux waveform
Loss Map enables to consider a DC bias
Jonas Mühlethaler
5
APEC 2015
Introduction
Application of Inductive Components (2) : Inductor of DAB Converter
(Non-Sinusoidal AC Current)
Current / Flux Waveform
Schematic
Modeling Difficulties
Solutions
-
-
-
Non-sinusoidal current / flux
waveform
Core losses occur in the interval of
constant flux
Mittwoch, 4. März 2015
Gecko-Simulations AG
-
FFT of current waveform for the
calculation of winding losses
Improved core loss equation that
considers relaxation effects
Jonas Mühlethaler
6
APEC 2015
Introduction
Application of Inductive Components (3) : Three-Phase PFC
(Sinusoidal Current + HF Ripple)
Current / Flux Waveform
Schematic
Modeling Difficulties
Solutions
-
-
-
Non-sinusoidal current / flux
waveform
Major loop and many (DC biased)
minor loops
-
Mittwoch, 4. März 2015
Gecko-Simulations AG
FFT of current waveform for the
calculation of winding losses
Determine core loss energy for each
segment and for each corner point in the
piecewise-linear flux waveform (-> minor
loop losses)
Add major loop losses
Jonas Mühlethaler
7
APEC 2015
Introduction
Overview of Different Flux Waveforms
Sinusoidal
DC Current +
HF Ripple
Non-Sinusoidal AC
Current
Minor Loop
Sinusoidal Current
+ HF Ripple
Major Loop
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
8
APEC 2015
Introduction
System Layer
Component Layer
Material Layer
www.ferroxcube.com
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
9
APEC 2015
Introduction
Overview of Other Modeling Issues
Flux Density
Distribution
Heat Dissipation
Core Type
Current
Distribution
Winding Type /
Arrangement
Mittwoch, 4. März 2015
Air Gap
Stray Field
Gecko-Simulations AG
Jonas Mühlethaler
10
APEC 2015
Introduction
Wide Range of Realization Options
Inductors / Transformers
Core Shapes
www.ferroxcube.com
Conductor Shapes
www.wagnergrimm.ch, www.ferroxcube.com
www.pack-feindraehte.de, www.jiricek.de
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
11
APEC 2015
Introduction
Modeling Inductive Components (1)
Procedure
1)
A reluctance model is introduced to describe the
electric / magnetic interface, i.e. L = f(i).
2)
Core losses are calculated.
Reluctance Model
3)
Winding losses are calculated.
4)
Inductor temperature is calculated.
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
12
APEC 2015
Introduction
Modeling Inductive Components (2)
The following effects are taken into consideration:
Magnetic Circuit Model (e.g. for Inductance Calculation):
Air gap stray field
Non-linearity of core material
Core Losses:
DC Bias
Different flux waveforms (link to circuit simulator)
Wide range of flux densities and frequencies
Different core shapes
Winding Losses:
Skin and proximity effect
Stray field proximity effect
Effect of core on magnetic field distribution
Litz, solid, and foil conductors
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
13
APEC 2015
Introduction
System Layer
Component Layer
Material Layer
www.ferroxcube.com
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
14
APEC 2015
Introduction
Motivation for an Accurate Loss Modeling : Multi-Objective Optimization (1)
PFC Rectifier with Input LCL filter
Filter Losses vs. Filter Volume
Converter Losses vs. Converter Volume
Converter =
Cooling System
+ Switches

Mittwoch, 4. März 2015
Sometime there are parameters that bring advantages for one subsystem while
deteriorating another subsystem (e.g. frequency in above example).
Gecko-Simulations AG
Jonas Mühlethaler
15
APEC 2015
Introduction
Motivation for an Accurate Loss Modeling : Multi-Objective Optimization (2)
Losses of a Loss-Optimized Design
Optimal Frequency
6 kHz
Mittwoch, 4. März 2015

In order to get an optimal system design, an overall system
optimization has to be performed.

It is (often) not enough to optimize subsystems independent
of each other.
Gecko-Simulations AG
Jonas Mühlethaler
16
APEC 2015
Outline

Magnetic Circuit Modeling

Core Loss Modeling

Winding Loss Modeling

Thermal Modeling

Multi-Objective Optimization

Summary & Conclusion
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
17
APEC 2015
Magnetic Circuit Modeling
Reluctance Model
Electric Network

Conductivity / Permeability
Resistance / Reluctance
Voltage / MMF
R  l / ( A)
V 
P2
 E ds
P1
I   J dA
Current / Flux
A
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
Magnetic Network

Rm  l / (  A)
Vm 
P2
 H ds
P1
   B dA
A
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APEC 2015
Magnetic Circuit Modeling
Why a Reluctance Model is Needed
A reluctance model is needed in order to
calculate the inductance ( L = N2/Rtot )
calculation the saturation current
calculate the air gap stray field
calculate the core flux density
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
Accurate loss modeling!
19
APEC 2015
Magnetic Circuit Modeling
Core Reluctance
Core Reluctance Dimensions
Reluctance Calculation
Rm 
Mittwoch, 4. März 2015
li
0 r Ai
Mean magnetic
length
Gecko-Simulations AG
Jonas Mühlethaler
Mean magnetic
cross-sectional
area
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APEC 2015
Magnetic Circuit Modeling
Air Gap Reluctance : Different Approaches (1)
Assumption of Homogeneous Field Distribution
Rm 
lg
0 Ag
lg Air gap length
lg
Ag Air gap cross-sectional area
a
Increase of the Air Gap Cross-Sectional Area
e.g. [1] (for a cross section with dimension a x t):
Rm 
a
a
[1]
Mittwoch, 4. März 2015
Gecko-Simulations AG
lg
0 (a  lg )(t  lg )
N. Mohan, T. M. Undeland, and W. P. Robbins - “Power
Electronics – Converter, Applications, and Design”,
John Wiley & Sons, Inc., 2003
Jonas Mühlethaler
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APEC 2015
Magnetic Circuit Modeling
Air Gap Reluctance : Different Approaches (2)
Schwarz-Christoffel Transformation
Transformation Equation v(t)
Transformation Equation z(t)
z (t ) 
l

 2 ln 1 

1  t  ln t  2 1  t

v(t ) 
V

ln t
(z and t are complex numbers)
[2]
K. J. Binns, P. J. Lawrenson, and C. W. Trowbridge, «The Analytical and Numerical Solution of Electric
and Magnetic Fields», John Wiley & Sons, Inc., 1992
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Magnetic Circuit Modeling
Air Gap Reluctance : Different Approaches (3)
Solution to 2-D problems found in literature, e.g. in [3]
Can’t be directly applied to 3-D problems.
Some 3-D solution to problem found in literature; however, they are complex [4] and/or
limited to one air gape shape [5]
More simple and universal model desired.
[3]
[4]
[5]
A. Balakrishnan, W. T. Joines, and T. G. Wilson - “Air-gap reluctance and inductance calculations for
magnetic circuits using a Schwarz-Christoffel transformation”, IEEE Transaction on Power Electronics,
vol. 12, pp. 654—663, July 1997.
P. Wallmeier, “Automatisierte Optimierung von induktiven Bauelementen für Stromrichteranwendungen”,
PhD Thesis, Universität – Gesamthochschule Paderborn, 2001.
E. C. Snelling, “Soft Ferrites - Properties and Applications”, 2nd edition, Butterworths, 1988
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Magnetic Circuit Modeling
Aim of New Model
Air gap reluctance calculation that
-
considers the three dimensionality,
-
is reasonable easy-to-handle,
-
is capable of modeling different shapes of air gaps,
-
while still achieving a high accuracy.
Illustration of Different Air Gap Shapes:
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Magnetic Circuit Modeling
New Model (1)
Basic Structure for the Air Gap Calculation (2-D) [3]
Next Core
Corner
R 'basic 
Mittwoch, 4. März 2015
1
w 2
 h 
 1  ln

4l  
 2l  
0 
Gecko-Simulations AG
Jonas Mühlethaler
25
APEC 2015
Magnetic Circuit Modeling
New Model (2)
Basic Structure for the Air Gap Calculation
2-D (1)
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Magnetic Circuit Modeling
Basic Structure for the Air Gap Calculation
New Model (3)
2-D (2)
Air Gap Type 1
R 'basic 
Air Gap Type 2
Mittwoch, 4. März 2015
1
w 2
 h 
 1  ln

4l  
 2l  
0 
Air Gap Type 3
Gecko-Simulations AG
Jonas Mühlethaler
27
APEC 2015
Magnetic Circuit Modeling
New Model (4)
2D  3D : Fringing Factor (1)
Illustrative Example
Air gap per
unit length
zy-plane
'
Rzy
'
Rzy
y 
lg
0 a
“Idealized” air gap
(no fringing flux)
zx-plane
'
zx
R
'
Rzx
x 
lg
0t
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Magnetic Circuit Modeling
New Model (5)
2D  3D : Fringing Factor (2)
3-D Fringing Factor:
   x y
Illustrative Example
Rg  
lg
0 at
“Idealized” air gap
(no fringing flux)
Alternative Interpretation:
Increase of air gap cross sectional area

1
x
1
y
A’
A
[6]

A’’
J. Mühlethaler, J.W. Kolar, and A. Ecklebe, “A Novel Approach for 3D Air Gap Reluctance Calculations”,
in Proc. of the ICPE - ECCE Asia, Jeju, Korea, 2011
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Magnetic Circuit Modeling
FEM Results
3-D FEM Simulation
Modeled Example
Results
a = 40 mm; h = 40 mm
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Magnetic Circuit Modeling
Experimental Results
Saturation Calculation
EPCOS E55/28/21, N = 80,
lg = 1 mm, Bsat = 0.45 T
Inductance Calculation
EPCOS E55/28/21, N = 80
Measurement
Isat = 3.7 A
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Magnetic Circuit Modeling
Non-Linearity of the Core Material
Flux and Reluctance Calculation
Inductance Calculation
This equation must be solved iteratively by
using a numerical solving method, e.g. the
Newton’s method.
Inductance
B-H Relation
0.74
1.5
21
1920
18
17
16
15
14
13
12
11
10
0.72
0.7 12
345678 91011213
14
15
Inductance [mL]
0.68
Magentic Flux Density [T]
Reluctance Model
16
0.66
17
0.64
18
0.62
19
1
9
8
7
6
0.5
5
4
0.6
20
3
2
0.58
21
0
Mittwoch, 4. März 2015
Gecko-Simulations AG
50
100
150
Current [A]
Jonas Mühlethaler
200
0 1
0
500
Magnetic Field [A/m]
1000
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APEC 2015
Example
Introduction
Schematic
Aim
Design PFC rectifier system.
Show trade-off between losses and volume.
Illustrative example.
Modeling of boost inductors (three individual inductors L2a = L2b = L2c) will
be step-by-step illustrated in the course of this presentation.
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Example
Reluctance Model (1)
Reluctance Model
Photo & Dimensions
Calculation of Core Reluctances

(2a )
do  2a
Rc1 
2 8
(2a )
0 r at
0  r t
2

(2  20mm)
60mm  2  20mm
A
8

2
 3654
(2  20mm)
0  20 '000  20mm  28mm
Vs
0  20 '000  28mm
2

(2a )
do  2a  2b
Rc2 
2 8
(2a )
0  r at
0  r t
2

(2  20mm)
60mm  2  20mm + 2  h
A
8

2
 12184
(2  20mm)
0  20 '000  20mm  28mm
Vs
0  20 '000  28mm
2
Material
Grain-oriented steel (M165-35S)
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Example
Reluctance Model (2)
Calculation Air Gap Reluctances
Photo & Dimensions
'
Rzy,1

zy-plane
1


 a
2
a
0 
  1  ln
l
l

2 g

4 g
 2

2



 
 
'
Rzy,2

1



 a
2
 (b  a )  
0 
 1  ln

l
 2 lg  
 
4 g
 2

2  
1
'
Rzy,3

 a
2
 b 
 1  ln


4lg  
 2lg  
0 
R
'
zy,1
'
'
 Rzy,2
 Rzy,3
'
'
'
Rzy,1
 Rzy,2
 Rzy,3
'
Rzy
 0.72
lg
y 
zx-plane
'
Rzy

0 a
'
Rzx,1

1


 t
2
a
0 
  1  ln
l
l

g
2

4 g

2
 2
'
Rzx




 
 
'
Rzx,2

1



 t
2
 (b  a )  
0 
 1  ln

l
 2 lg  
 
4 g

2  
 2
'
'
Rzx,1
 Rzx,2
Basic Reluctance
x 
2
Rg   x y
'
Rzx
 0.84
lg
0t
lg
0 at
 1.66
MA
Wb
Inductance
Material
Grain-oriented steel (M165-35S)
Mittwoch, 4. März 2015
R 'basic 
1
L
w 2
 h 
 1  ln

4l  
 2l  
0 
Gecko-Simulations AG
Jonas Mühlethaler
N2
 2.66mH
Rc1  Rc2  Rg1  Rg2
meas.
2.69 mH
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APEC 2015
Outline

Magnetic Circuit Modeling

Core Loss Modeling

Winding Loss Modeling

Thermal Modeling

Multi-Objective Optimization

Summary & Conclusion
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Core Loss Modeling
Overview of Different Core Materials (1)
Magnetic
Materials
Soft Magnetic
Materials
Hard Magnetic
Materials
Iron Based Alloys
Ferrites
- ferromagnetics -
- ferrimagnetics -
Alloys with some amount of Si, Ni, Cr or Co.
Low electric resistivity.
High saturation flux density.
Ceramic materials, oxide mixtures of iron and Mn, Zn, Ni or Co.
High electric resistivity.
Small saturation flux density compared to ferromagnetics.
Laminated Cores
Laminations are electrically isolated to
reduce eddy currents.
Mittwoch, 4. März 2015
Powder Iron Cores
Amorphous Alloys
Nanocrystalline Materials
Consist of small iron particles, which are
electrically isolated to each other.
Made of alloys without crystallyine order
(cf. glasses, liquids).
Ultra fine grain FeSi, which are
embedded in an amorphous minority
phase.
Gecko-Simulations AG
Jonas Mühlethaler
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APEC 2015
Core Loss Modeling
Overview of Different Core Materials (2)
Selection Criteria
Ferrite
Powder Iron Core
Saturation Flux Density
Low Sat. Flux Density (0.45 T)
High Sat. Flux Density (1.5 T)
Power Loss Density
Low Losses
Moderate Losses
(Frequency Range)
Low Price
Low Price
Price
Many Different Shapes
Many Different Shapes
etc.
Very Brittle
Distributed Air Gap (low rel. permeability)
Laminated Steel Cores
Amorphous Alloys
Nanocrystalline Materials
Very High Sat. Flux Density (2.2T)
High Sat. Flux Density (1.5T)
High Sat. Flux Density (1.1T)
High Losses
Low Losses
Very Low Losses
Low Price
High Price
Very High Price
Many Different Shapes
Limited Available Shapes
Limited Available Shapes
LF: BSAT = Bmax.
HF: Bmax is limited by core losses.
Mittwoch, 4. März 2015
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APEC 2015
Core Loss Modeling
Overview of Different Core Materials (3)
[7]
[7]
M. S. Rylko, K. J. Hartnett, J. G. Hayes, M.G. Egan, “Magnetic Material Selection for High Power High Frequency
Inductors in DC-DC Converters”, in Proc. of the APEC 2009.
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APEC 2015
Core Loss Modeling
Physical Origin of Core Losses (1)
Weiss Domains / Domain Walls
-
Spontaneous magnetization.
Material is divided to saturated domains
(Weiss domains).
In case an external field is applied, the
domain walls are shifted or the magnetic
moments within the domains change their
direction.  The net magnetization becomes
greater than zero.
B-H-Loop
-
-
Mittwoch, 4. März 2015
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The flux change is partly irreversible, i.e.
energy is dissipated as heat.
The reason for this are the so called
Barkhausen jumps, that lead to local eddy
current losses.
In case the loop is traversed very slowly,
these Barkhausen jumps lead to the static
hysteresis losses.
Jonas Mühlethaler
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APEC 2015
Core Loss Modeling
Physical Origin of Core Losses (2)
B-H-Loop
Mittwoch, 4. März 2015
Gecko-Simulations AG
-
If the process would be fully reversible,
going from B1 to B2 would store potential
energy in the magnetic material that is later
released (i.e. the area of the closed loop
would be zero).
-
Since the process is partly irreversible, the
area of the closed loop represents the
energy loss per cycle
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APEC 2015
Core Loss Modeling
Classification of Losses (1)

(Static) hysteresis loss

Rate-independent BH Loop.

Loss energy per cycle is constant.

Irreversible changes each within a small
region of the lattice (Barkhausen jumps).

These rapid, irreversible changes are
produced by relatively strong local fields within
the material.

Eddy current losses

Residual Losses – Relaxation losses
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APEC 2015
Core Loss Modeling
Classification of Losses (2)

(Static) hysteresis loss

Eddy current losses

Depend on material conductivity and core
shape.

Affect BH loop.

Residual Losses – Relaxation losses
Measurements
VITROPERM 500F
0.4
0.3
0.2
i [A]
0.1
0
-0.1
-0.2
-0.3
-0.4
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
0
2
4
6
8
10
t [s]
12
14
16
18
20
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APEC 2015
Core Loss Modeling
Classification of Losses (3)

(Static) hysteresis loss

Eddy current losses

Residual losses – Relaxation losses

Rate-dependent BH Loop.

Reestablishment of a thermal equilibrium is
governed by relaxation processes.

Restricted domain wall motion.
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APEC 2015
Core Loss Modeling
Typical Flux Waveforms
Sinusoidal
e.g. 50/60 Hz isolation transformer
Triangular
e.g. Buck / Boost converter
Trapezoidal
e.g. boost inductor of Dual Active
Bridge
Combination
e.g. Boost inductor in PFC
Mittwoch, 4. März 2015
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45
APEC 2015
Core Loss Modeling
Outline of Different Modeling Approaches
Steinmetz Approach
Loss Map Approach
P  k f α Bβ
(Loss Database)
-
Simple
Steinmetz parameter
are valid only in a
limited flux density
and frequency range
DC Bias not
considered
(Only for sinusoidal
flux waveforms)
-
Loss Separation
Hysteresis Model
(e.g. Preisach Model, Jiles-Atherton
Model)
P  Physt  Peddy  Presidual
-
Needed parameters often unknown
Model is widely applicable
Increases physical understanding of loss
mechanisms
Mittwoch, 4. März 2015
Measuring core losses is
indispensable to overcome limits of
Steinmetz approach
wwww.epcos.com
-
Gecko-Simulations AG
-
Jonas Mühlethaler
Difficult to parameterize
Increases physical understanding of loss
mechanisms
46
APEC 2015
Core Loss Modeling
Overview of Hybrid Modeling Approach
“The best of both worlds” (Steinmetz & Loss Map approach)
Outline of Discussion
(2)/(3)
Loss Map
(Loss Material Database)
-
-
-
Derivation of the
i2GSE. (1)
How to measure core
losses in order to
build loss map. (2)
Use of loss map. (3)
How to calculate core
losses for cores of
different shapes? (4)
k , ki ,  ,  ,  r , r , qr ,
T
1
dB
Pv   ki
T 0 dt
Mittwoch, 4. März 2015

Gecko-Simulations AG
B 
 
n
dt   Qrl Prl
l 1
Jonas Mühlethaler
(1)
P
V
(4)
47
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Motivation (1)
Steinmetz Equation SE
Pv  k f α Bˆ β
-
Pv :
Only sinusoidal waveforms ( iGSE).
iGSE
T
1
dB
Pv   ki
T 0 dt
ki 

 B 
 
time-average
power loss per
unit volume
dt
k
(2 ) 1 
2
0

cos  2  d
- DC bias not considered
- Relaxation effect not considered ( i2GSE)
- Steinmetz parameter are valid only for a limited flux density and
frequency range
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48
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Motivation (2)
iGSE [8]
T
1
dB
Pv   ki
T 0 dt
ki 

 B 
 
Idea
- Generalized formula that is applicable for
different flux waveforms
- Losses depend on dB/dt
dt
k
(2 ) 1 
2
0

cos  2  d
For Sinusoidal Waveforms
T
1
dB
Pv   ki
T 0 dt
How to apply the formula?
k
Pv  i
T

 B 
 
 B 
dt  kf  

 2 





 B 
 
 
 B 
 DT 
  B    ...
  B   (1  D)T 
 DT 


 (1  D)T 
[8] K. Venkatachalam, C. R. Sullivan, T. Abdallah, and H. Tacca, “Accurate prediction of ferrite core loss with nonsinusoidal
waveforms using only Steinmetz parameters”, in Proc. of IEEE Workshop on Computers in Power Electronics, pp. 36-41, 2002.
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49
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Motivation (3)
Waveform
Results
iGSE
Conclusion
T
1
dB
Pv   ki
T 0 dt
Mittwoch, 4. März 2015

 B 
 
dt
Gecko-Simulations AG
Losses in the phase of constant flux!
Jonas Mühlethaler
50
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – B-H-Loop
Relaxation Losses

Rate-dependent BH Loop.

Reestablishment of a thermal
equilibrium is governed by
relaxation processes.

Restricted domain wall motion.
Current Waveform
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51
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Model Derivation 1 (1)
Derivation (1)
Waveform
Relaxation loss energy can be described with
t
1 


E  E 1  e 


Loss Energy per Cycle
 is independent of operating point.
How to determine E?
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52
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Model Derivation 1 (2)
E – Measurements
Waveform
Conclusion
 E follows a power
function!
d
E  kr B(t )
dt
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r
B 
r
53
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Model Derivation 1 (3)
Model Part 1
T
1
dB
Pv   ki
T 0 dt

B 
1 d
Prl  k r B(t )
T dt
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Gecko-Simulations AG
 
n
dt   Prl
l 1
r
B 
r
t
1 

1  e  




Jonas Mühlethaler
54
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Model Derivation 2 (1)
Waveform
Power Loss
Explanation
1)
2)
3)
4)
For values of D close to 0 or close to 1 a loss underestimation is expected when calculating losses with iGSE (no
relaxation losses included).
For values of D close to 0.5 the iGSE is expected to be accurate.
Adding the relaxation term leads to the upper loss limit, while the iGSE represents the lower loss limit.
Losses are expected to be in between the two limits, as has been confirmed with measurements.
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55
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Model Derivation 2 (2)
Waveform
Model Adaption
T
1
dB
Pv   ki
T 0 dt

B 
 
n
dt   Qrl Prl
l 1
Qrl should be 1 for D = 0
Qrl should be 0 for D = 0.5
Power Loss
Qrl should be such that calculation fits a triangular
waveform measurement.
Qrl  e
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 qr
dB ( t  ) / dt
dB ( t  ) / dt
 qr 1DD 
 e





56
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Model Derivation 2 (3)
Waveform
Mittwoch, 4. März 2015
Power Loss
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Jonas Mühlethaler
57
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Summary
The improved-improved Generalized Steinmetz Equation (i2GSE) [9]
T
1
dB
Pv   ki
T 0 dt

B 
with
1 d
Prl  k r B(t )
T dt
and
Qrl  e
[9]
 qr
 
n
dt   Qrl Prl
l 1
r
B 
r
t
1 


1  e 




dB ( t  ) / dt
dB ( t  ) / dt
J. Mühlethaler, J. Biela, J.W. Kolar, and A. Ecklebe, “Improved Core Loss Calculation for Magnetic
Components Employed in Power Electronic Systems”, in Proc. of the APEC, Ft. Worth, TX, USA, 2011.
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58
APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Example
i2GSE
Evaluated for each piecewise-linear flux
segment
T
1
dB
Pv   ki
T 0 dt
Example
Pv 
Evaluated for each voltage step, i.e. for each
corner point in a piecewise-linear flux
waveform.
T  2t
T
Mittwoch, 4. März 2015

B 
 
n
dt   Qrl Prl
l 1
 B
T 2  t


dB 0

B
dt 

 T 2  t

0
B
ki
T 2  t

 B 
 
for t  0 and t  T 2  t
for t  T 2  t and t  T 2
for t  T 2 and t  T  t
for t  T  t and t  T
2
  Qrl Prl
with
l 1
Gecko-Simulations AG
Qr1 = Qr2 = 0
1
B
Pr1  Pr2  kr
T T 2  t
Jonas Mühlethaler
r
 B 
r
t


1  e 

59



APEC 2015
Core Loss Modeling
Derivation of the i2GSE – Conclusion
Evaluated for each piecewise-linear flux
segment
i2GSE
T
1
dB
Pv   ki
T 0 dt

B 
 
n
dt   Qrl Prl
l 1
Evaluated for each voltage step, i.e. for each
corner point in a piecewise-linear flux
waveform.
Remaining Problems
Steinmetz parameter are valid only in a limited flux density and frequency range.
Core Losses vary under DC bias condition.
Modeling relaxation and DC bias effects need parameters that are not given by core material
manufacturers.
Measuring core losses is indispensable!
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60
APEC 2015
Core Loss Modeling
Overview of Hybrid Modeling Approach
“The best of both worlds” (Steinmetz & Loss Map approach)
Outline of Discussion
(2)/(3)
Loss Map
(Loss Material Database)
-
-
-
Derivation of the
i2GSE. (1)
How to measure core
losses in order to
build loss map. (2)
Use of loss map. (3)
How to calculate core
losses for cores of
different shapes? (4)
k , ki ,  ,  ,  r , r , qr ,
T
1
dB
Pv   ki
T 0 dt
Mittwoch, 4. März 2015

Gecko-Simulations AG
B 
 
n
dt   Qrl Prl
l 1
Jonas Mühlethaler
(1)
P
V
(4)
61
APEC 2015
Core Loss Modeling
Core Loss Measurement – Measurement Principle
Waveforms
Excitation System
Schematic
Sinusoidal
Triangular
Trapezoidal
Voltage
0 … 450 V
Current
0 … 25 A
Frequency 0 … 200 kHz
Loss Extraction
1
B(t ) 
N 2  Ae
t
 u ( ) d
0
P[W ]
V [ m3 ]
N  i (t )
H (t )  1
le
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62
APEC 2015
Core Loss Modeling
Core Loss Measurement - Overview
System Overview
P/V
T
N
f  i1 (t ) 1 v2 (t ) dt
f
N
P
2
 0

V
Aele
Mittwoch, 4. März 2015
T

0
H (t )le N1
dB(t )
N 2 Ae
dt
N1 N 2
dt
 f
Aele
Gecko-Simulations AG
Jonas Mühlethaler

B (T )
B (0)
H ( B)dB
63
APEC 2015
Core Loss Modeling
Overview of Hybrid Modeling Approach
“The best of both worlds” (Steinmetz & Loss Map approach)
Outline of Discussion
(2)/(3)
Loss Map
(Loss Material Database)
-
-
-
Derivation of the
i2GSE. (1)
How to measure core
losses in order to
build loss map. (2)
Use of loss map. (3)
How to calculate core
losses for cores of
different shapes? (4)
k , ki ,  ,  ,  r , r , qr ,
T
1
dB
Pv   ki
T 0 dt
Mittwoch, 4. März 2015

Gecko-Simulations AG
B 
 
n
dt   Qrl Prl
l 1
Jonas Mühlethaler
(1)
P
V
(4)
64
APEC 2015
Core Loss Modeling
Needed Loss Map Structure
Typical flux waveform
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Content of Loss Map
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65
APEC 2015
Core Loss Modeling
Minor and Major Loops
Idea
Minor Loop
Major Loop
Implementation
P
 
 V  Major
P
 Piecewise Linear
 V Segment (+ Turning Point)
Losses due to Minor and Major
Loops are calculated independent
of each other and summed up.
Actually, it is not considered how
the minor loop closes: each
piecewise linear segment is
modeled as having half the losses
of its corresponding closed loop
(cf. next slides).
P P
P
 
  
Piecewise Linear
V  V Major
 V Segment
(+ Turning Point)
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66
APEC 2015
Core Loss Modeling
Hybrid Loss Modeling Approach (1)
HDC / BDC
(I)
(II)
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67
APEC 2015
Core Loss Modeling
Evaluated for the according corner point
in a piecewise-linear flux waveform.
Hybrid Loss Modeling Approach (2)
Evaluated for the according piecewiselinear flux segment
Loss Map
T
1
dB
Pv   ki
T 0 dt

B 
 
n
dt   Qrl Prl
l 1
(I)
(II)
Three loss map
operating points
are required in
order to extract
the parameters ,
, and k (or ki).
Pv1  ki  2 f1 
 B1 


Pv2  ki  2 f 2   B2 


Pv3  ki  2 f3   B3 


P
V
These equations arise when one evaluates the
i2GSE for symmetric triangular waveforms.
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68
APEC 2015
Core Loss Modeling
Hybrid Loss Modeling Approach (3)
Interpolation and Extrapolation
(HDC*, T*, B*, f*)
HDC and T
B and f
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69
APEC 2015
Core Loss Modeling
Hybrid Loss Modeling Approach (4)
Advantages of Hybrid Approach (Loss Map and i2GSE):
Relaxation effects are considered (i2GSE).
A good interpolation and extrapolation between premeasured operating points is achieved.
Loss map provides accurate i2GSE parameters for a wide frequency and flux density range.
A DC bias is considered as the loss map stores premeasured operating points at different DC
bias levels.
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Jonas Mühlethaler
70
APEC 2015
Core Losses
Summary of Loss Density Calculation
Sinusoidal
P  k f α Bβ
T
1
dB
Pv   ki
T 0 dt
Triangular

B 
 
n
dt   Qrl Prl
l 1
with Q  0, n = 1
T
Trapezoidal
1
dB
Pv   ki
T 0 dt

B 
 
n
dt   Qrl Prl
l 1
with Q = 1, n = 2
Combination
T
1
dB
Pv   ki
T 0 dt

B 
 
n
dt   Qrl Prl
l 1
with different Q’s and n >> 0.
Mittwoch, 4. März 2015
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71
APEC 2015
Core Loss Modeling
Overview of Hybrid Modeling Approach
“The best of both worlds” (Steinmetz & Loss Map approach)
Outline of Discussion
(2)/(3)
Loss Map
(Loss Material Database)
-
-
-
Derivation of the
i2GSE. (1)
How to measure core
losses in order to
build loss map. (2)
Use of loss map. (3)
How to calculate core
losses for cores of
different shapes? (4)
k , ki ,  ,  ,  r , r , qr ,
T
1
dB
Pv   ki
T 0 dt
Mittwoch, 4. März 2015

Gecko-Simulations AG
B 
 
n
dt   Qrl Prl
l 1
Jonas Mühlethaler
(1)
P
V
(4)
72
APEC 2015
Core Loss Modeling
Effect of Core Shape
Procedure
Reluctance Model
1)
The flux density in every core section of
(approximately) homogenous flux density
is calculated.
2)
The losses of each section are calculated.
3)
The core losses of each section are then
summed-up to obtain the total core
losses.
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73
APEC 2015
Core Loss Modeling
Effective Core Dimensions of Toroid
Motivation for Effective Core Dimensions
Core loss densities are needed to model core
losses. It is difficult to determine these loss
densities from a toroid, since the flux density is not
distributed homogeneously in a toroid.
Illustration
Definition: Ideal Toroid
A toroid is ideal when he has a homogenous flux
density distribution over the radius (r1  r2).
Idea for Real Toroid
Find effective core magnetic length and cross
section, so one can calculate as if it were an ideal
toroid, i.e. as if the flux density distribution were
homogenous.
Effective magnetic length
Effective magnetic cross-section
Mittwoch, 4. März 2015
le 
2 ln r2 / r1
1/ r1  1/ r2
h ln 2 r2 / r1
Ae 
1 / r1  1 / r2
Gecko-Simulations AG
Jonas Mühlethaler
74
APEC 2015
Core Loss Modeling
Impact of Core Shape on Eddy Current Losses
Eddy current loss density can be determined as [5]
Peddy
ˆ )2
( Bfd

kec 
Peddy
ˆ )2
( Bfd

6
For a laminated core it is

The eddy current losses per unit volume depend not on the shape of the bulk material, but on
the size and geometry of the insulated regions.

In case of laminated iron cores, it is still appropriate to calculate with core loss densities that
have been measured on a sample core with a geometrically different bulk material, but with the
same lamination or tape thickness.
[5]
E. C. Snelling, “Soft Ferrites - Properties and Applications”, 2nd edition, Butterworths, 1988
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APEC 2015
Core Loss Modeling
Effect in Tape Wound Cores
www.vacuumschmelze.de
Thin ribbons (approx. 20m)
Wound as toroid or as double C core.
Amorphous or nanocrystalline materials.
Losses in gapped tape wound cores higher than expected!
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76
APEC 2015
Core Loss Modeling
Effect in Tape Wound Cores - Cause 1 : Interlamination Short Circuits
Machining process
Surface short circuits introduced by machining
(particular a problem in in-house production).
After treatment may reduce this effect. At ETH, a core was put in an 40% ferric chloride FeCl3
solution after cutting, which substantially (more than 50%) decreased the core losses.
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77
APEC 2015
Core Loss Modeling
Effect in Tape Wound Cores - Cause 2 : Orthogonal Flux Lines (1)
Eddy
current
Fringing flux
Main flux
Eddy
current
A flux orthogonal to the ribbons leads to very high eddy current losses!
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78
APEC 2015
Core Loss Modeling
Effect in Tape Wound Cores - Cause 2 : Orthogonal Flux Lines (2)
An experiment that illustrates well the loss increase due to an orthogonal flux is given here.
Displacements
Horizontal Displacement
Vertical Displacement
Core Loss Results
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APEC 2015
Core Loss Modeling
Effect in Tape Wound Cores - Cause 2 : Orthogonal Flux Lines (3)
Core loss increase due to leakage flux in transformers.
Results
Secondary
Winding
Primary
Winding
Core Losses (W)
Measurement Set Up
12
10
A higher load
current leads to
higher orthogonal
flux!
8
6
4
0
1
2
3
Secondary Current (A)
4
FEM
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80
APEC 2015
Core Loss Modeling
Effect in Tape Wound Cores - Cause 2 : Orthogonal Flux Lines (4)
In [10] a core loss increase with increasing air gap length has been observed.
Figures from [10]
[10]
H. Fukunaga, T. Eguchi, K. Koga, Y. Ohta, and H. Kakehashi, “High Performance Cut Cores Prepared From
Crystallized Fe-Based Amorphous Ribbon”, in IEEE Transactions on Magnetics, vol. 26, no. 5, 1990.
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Example
Core Loss Modeling (1)
Photo & Dimensions
Flux Density Distribution
Reluctance Model
An approximately homogeneous
flux density distribution inside the core.
Flux Density Waveform
GeckoMAGNETICS
Presentation
Material
Grain-oriented steel (M165-35S)
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82
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Example
Core Loss Modeling (2)
SiFe vs. Ferrite
2 kHz vs. 20 kHz
Modeling with GeckoMAGNETICS
APEC 2015
Example
Core Loss Modeling (3)
2 kHz / Tmax = 65 °C / L = 2.5 mH / Solid Round Wires
SiFe (M165-35S)
Ferrite (N87)
Sat. Limit
APEC 2015
Example
Core Loss Modeling (4)
20 kHz / Tmax = 65°C / L = 1 mH / Litz Wires
SiFe (M165-35S)
Ferrite (N87)
Therm. Limit
APEC 2015
Example
Core Loss Modeling (5)
19.02.14
Gecko-Simulations AG
Jonas Mühlethaler
86
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Outline

Magnetic Circuit Modeling

Core Loss Modeling

Winding Loss Modeling

Thermal Modeling

Multi-Objective Optimization

Summary & Conclusion
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87
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Winding Loss Modeling
Skin Effect (1)
H-field in conductor
Ampere’s Law
Induced Eddy Currents
Faraday’s Law
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88
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Winding Loss Modeling
Skin Effect (2)
FEM Simulation
50 Hz
5 kHz
20 kHz
100 kHz
Current Distribution
Outer radius of
conductor
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89
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Winding Loss Modeling
Skin Effect (3)
Skin Depth
 
(, where the current density has 1/e of surface value)
1
[19]
0 f
Power Loss Increase with Frequency
PS  FR ( f )  RDC  Iˆ2
FR ( f )

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d
2
90
APEC 2015
Winding Loss Modeling
Skin Effect (4)
Current Distributions
Parallel-connected (not
twisted) conductors!
Figure from [19]
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91
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Winding Loss Modeling
Proximity Effect (1)
H-field of neighboring conductor induces eddy currents
Ampere’s Law
Faraday’s Law
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92
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Winding Loss Modeling
Proximity Effect (2)
Eddy Currents in
Conductor
50 Hz
5 kHz
15 kHz 100 kHz
Induced Eddy
Currents
(He,rms = 35 A/m
parallel to
conductor)
Current
Concentration
I
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I
I
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I
Figures from [19]
93
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Winding Loss Modeling
Skin vs. Proximity Effect
Situation
Results
(f = 100 kHz, Ipeak = 1 A, He,peak = 1000 A/m)
Conductor length l = 1 m
PTotal
PProx
PSkin
Definition
Skin Effect Losses PSkin
Losses due to current I, including loss increase
due to self-induced eddy currents.
Proximity Effect Losses PProx
Losses due to eddy currents induced by external
magnetic field He.
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94
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Winding Loss Modeling
Litz Wire (1) - What are Litz wires?
Idea
Advantages of Litz wires
HF losses can be reduced
substantially
Disadvantages of Litz wires
High price
Heat dissipation difficult
Higher RDC
www.wikipedia.org
Implementation
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95
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Winding Loss Modeling
Litz Wire (2) - Why Litz Wires Have to be Twisted? (1)
Bundle-Level Skin Effect
Current Distributions
Internal Proximity
Effect
(will be explained later)
(Ampere’s Law)
(Faraday’s Law)
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96
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Winding Loss Modeling
Litz Wire (3) - Why Litz Wires Have to be Twisted? (2)
Bundle-Level Proximity Effect
(Ampere’s Law)
Figures from [19]
(Faraday’s Law)
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97
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Winding Loss Modeling
Litz Wire (4) – Strand-Level Effects
Internal and External Fields lead to Internal and External Proximity Effects
Losses in Litz Wires
Losses in Solid Wires
l=1m
l=1m
Internal prox. effect
Skin effect
Skin effect
Ext. prox. effect
Prox. effect
(25 x di = 0.5 mm, Ipeak = 5 A, He,peak = 300 A/m)
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(d = 2.5 mm, Ipeak = 5 A, He,peak = 300 A/m)
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98
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Winding Loss Modeling
Litz Wire (5) – Types of Eddy-Current Effects in Litz Wire
Figure from [11]
Mittwoch, 4. März 2015
Ch. R. Sullivan, “Optimal Choice for Number of Strands in a Litz-Wire Transformer
Winding”, in IEEE Transactions on Power Electronics, vol. 14, no. 2, 1999.
Gecko-Simulations AG
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99
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Winding Loss Modeling
Litz Wire (6) – Real Litz Wire
Worst Case Litz Wire
(parallel connected
strands, no twisting)
Ideal Litz Wire
(ideally twisted
strands)
Operating Point
f = 20 kHz / n = 130 /
di = 0.4 mm
How do “real” Litz wires behave? [12]
Skin Effect / Internal Proximity Effect
External Proximity Effect
Litz Wire Type 1:
Litz Wire Type 2:
Rskin,λ  skin Rskin,ideal  (1  skin ) Rskin,parallel
Rprox,λ  prox Rprox,ideal  (1  prox ) Rprox,parallel
7 bundles with 35 strands each: 
4 bundles with 61/62 strands each:
skin  0.5 / prox  0.99
skin  0.9 / prox  0.99
[12] H. Rossmanith, M. Doebroenti, M. Albach, and D. Exner, “Measurement and Characterization of High Frequency Losses in Nonideal
Litz Wires”, IEEE Transactions on Power Electronics, vol. 26, no. 11, November 2011
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100
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Winding Loss Modeling
Litz Wire (7) - Are Litz Wires Better than Solid Conductors?
Skin and Internal
Proximity Effect
l=1m
Solid Wire
(d = 2.5 mm, Ipeak = 5 A)
Litz Wire
(25 x di = 0.5 mm, Ipeak = 5 A)
Litz Wire
(50 x di = 0.35 mm, Ipeak = 5 A)
Litz Wire
(100 x di = 0.25 mm, Ipeak = 5 A)
External Proximity
Effect
l=1m
Litz Wire of 25 strands with
d = 0.5mm
Solid Wire with d = 2.5 mm
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101
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Winding Loss Modeling
Foil Windings Enclosed by Magnetic Material
Conductor length l = 1 m
d = 1.95 mm
Ipeak = 1 A
Same cross
section!
10 mm x 0.3 mm
Ipeak = 1 A
Advantages of foil windings
HF losses can be reduced
Lower price compared to Litz wire
High filling factor
“Skin” of foil conductor larger
than of round conductor with
same cross section; hence,
skin effect losses lower in foil
conductor.
Disadvantages of foil windings
Increased winding capacitance
Risk of orthogonal flux
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102
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Winding Loss Modeling
Foil Windings Not Enclosed by Magnetic Material (1)
Single Conductor
10 mm x 0.3 mm
Ipeak = 1 A
Three Conductors
l=1m
d = 1.95 mm
Ipeak = 1 A
10 mm x 0.3 mm
Ipeak = 1 A
l=1m
d = 1.95 mm
Ipeak = 1 A
FEM @ 8 kHz
Orthogonal flux leads to
increased skin and
proximity effect.
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Orthogonal Flux!
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Winding Loss Modeling
Foil Windings Not Enclosed by Magnetic Material (2)
(Foil) Windings with Return Conductors
l=1m
d = 1.95 mm
Ipeak = 1 A
10 mm x 0.3 mm
Ipeak = 1 A
FEM @ 8 kHz
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104
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Winding Loss Modeling
Overview About Different Winding Types
Type
Price
Skin & Proximity
Filling Factor
Heat Dissipation
Round Solid Wire
++
--
+
+
Litz Wire
--
++
-
--
Foil Winding
+
+
++
+
Rectangular Wire
++
-
++
+
Rectangular Wire
Foil windings are better
only in this region!
Round conductor
P0 … round conductor
Table and Figure from [13] M. Albach, “Induktive Komponenten in der Leistungselektronik”, VDE Fachtagung - ETG Fachbereich Q1
"Leistungselektronik und Systemintegration", Bad Nauheim, 14.04.2011
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105
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Winding Loss Modeling
Skin Effect of Foil Conductor
PS  FF ( f )  RDC  Iˆ2
Geometry Considered
(Loss per unit length)
with
v sinh v  sin v
4 cosh v  cos v
1
RDC 
 bh
h
v
FF 

 
Current Distribution
1
0 f
FF evaluated
[19]
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106
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Winding Loss Modeling
Proximity Effect of Foil Conductor
ˆ2
PP  GF ( f )  RDC  H
S
Geometry Considered
(Loss per unit length)
with
sinh v  sin v
cosh v  cos v
1
RDC 
 bh
h
v
GF  b 2 v

 
1
0 f
Current Distribution
GF evaluated
[19]
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(b = 1 m)
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Winding Loss Modeling
Skin Effect of Solid Round Conductor
Geometry Considered
PS  FR ( f )  RDC  Iˆ2
(Loss per unit length)
with
FR evaluated
4
 d 2
d

2
1
 
0 f
RDC 
FR 
 ber0 ( )bei1 ( )  ber0 ( )ber1 ( ) bei 0 ( )ber1 ( )  bei 0 ( )bei1 ( ) 



2
2
ber
(

)

bei
(

)
ber1 ( ) 2  bei1 ( ) 2
4 2
1
1

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
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108
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Winding Loss Modeling
Proximity Effect of Solid Round Conductor
Geometry Considered
PP  GR ( f )  RDC  Hˆ S2
(Loss per unit length)
with
GR evaluated
4
 d 2
d

2
1
 
0 f
RDC 
GR  
(d = 1 m)
 2 d 2  ber2 ( )ber1 ( )  ber2 ( )bei1 ( ) bei 2 ( )bei1 ( )  bei 2 ( )ber1 ( ) 



ber0 ( ) 2  bei 0 ( ) 2
ber0 ( ) 2  bei 0 ( ) 2
2 2 

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109
APEC 2015
Winding Loss Modeling
Skin and Proximity Effect of Litz Wire
 Iˆ 
PS  n  RDC  FR ( f )   
n
Skin Effect
2
(Loss per unit length)
Losses in Litz Wires
Proximity Effect
l=1m
PP  PP,e  PP,i


Iˆ
 n  RDC  GR ( f )   H e2 
2 2 
2

da 

Internal prox. effect
2
Skin effect
Ext. prox. effect
(Loss per unit length)
Average internal field Hi
under the assumption of a
homogeneous current
distribution inside the Litz
wire.
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(25 x di = 0.5 mm, Ipeak = 5 A, He,peak = 300 A/m)
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110
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Winding Loss Modeling
Orthogonality of Winding Losses
It is valid to calculate the losses for
each frequency component
independently and total them up.

P   ( PS,i  PP,i )
i 0
It is valid to calculate the skin and
proximity losses independently and
total them up.
[14]
J. A. Ferreira, “Improved analytical modeling of conductive losses in magnetic components”, in
IEEE Transactions on Power Electronics, vol. 9, no. 1, 1994.
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111
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Winding Loss Modeling
Calculation of External Field He (1D - Approach)
Un-Gapped Transformer Cores
M


2
2
ˆ
P  RDC  FR/F I NM  NGR/F  Hˆ avg,m
 lm
m 1


with
H avg 
1
 H left  H right 
2
it is
4M 2  1 
2
3
ˆ
P  RDC I  FR/F NM  N MGR/F
 lm
2
12
b

F

where
H left H avg
N … the number of conductors per layer
(i.e. N = 1 for foil windings)
H right
M … the number of layers.
(Ampere’s Law)
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Figure from [19]
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112
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Winding Loss Modeling
Short Foil Conductors
“Porosity Factor”

NbL
bF
Redefinition of Parameters
 '  
 '
1
 f  ' 0
 '
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h
'
113
APEC 2015
Winding Loss Modeling
FEM Simulations : Foil Windings
N = 2 x 10
h = 0.3 mm
bL = 33 mm
bF = 37 mm
Ipeak = 1 A
N=2x7
h = 0.4 mm
bL = 37 mm
bF = 37 mm
Ipeak = 1 A
Error < 6.5%
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114
APEC 2015
Winding Loss Modeling
Calculation of External Field He (2D - Approach)
Gapped cores: 2D approach is necessary !
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115
APEC 2015
Winding Loss Modeling
Effect of the Air Gap Fringing Field
The air gap is replaced by a fictitious
current, which …
… has the value equal to the magneto-motive
force (mmf) across the air gap.
P2
P2
I
P1
P1
Vm,air 
P2
 Hdl    R
air
P1
Vm,air 
P2
 Hdl  I
P1
 An accurate air gap reluctance model is needed!
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116
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Winding Loss Modeling
Effect of the Core Material
The method of images (mirroring)
“Pushing the walls away”
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117
APEC 2015
Winding Loss Modeling
Calculation of External Field He (2D - Approach)
Gapped cores: 2D approach
Winding Arrangement
External field vector across conductor qxi;yk
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118
APEC 2015
Winding Loss Modeling
Different Winding Sections
Section 1
Many mirroring steps
necessary in order to push
the walls away.
Section 2
Only one mirroring step
necessary (only one wall).
Normally, higher proximity losses in Section 1.
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119
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Winding Loss Modeling
FEM Simulations : Round Windings (Including Litz Wire Windings) (1)
Major Simplification
-
magnetic field of the induced eddy
currents neglected.
-
This can be problematic at frequencies
above (rule-of-thumb) [15]
f max 
2.56
0 d 2
Results of considered winding arrangements
[15]
f-range
f < fmax
f > fmax
Error
< 5%
> 5% (always < 25%)
A. Van den Bossche, V. C. Valchev, “Inductors and Transformers for
Power Electronics”, CRC Press. Taylor & Francis Group, 2005
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120
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Winding Loss Modeling
FEM Simulations : Round Windings (Including Litz Wire Windings) (2)
Results
FEM Simulation
f max
f max
f max
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Winding Loss Modeling
Methods to Decrease Winding Losses (1)
Interleaving
Optimal Solid Wire Thickness
l=1m
PTotal
PProx
PSkin
[19]
Optimal Foil Thickness
l=1m
PTotal
(f = 100 kHz, Ipeak = 1 A, He,peak = 1000 A/m)
PProx
Litz Wire
PSkin
l=1m
 Increase number
of strands.
(resp.: find optimal
number of strands)
(f = 20 kHz, Ipeak = 1 A, b = 20 cm, He,peak = 1000 A/m)
Avoid Orthogonal Flux in Foil Windings
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Push this point to
higher frequencies!
Jonas Mühlethaler
122
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Winding Loss Modeling
Methods to Decrease Winding Losses (2)
Arrangement of Windings
Proximity losses increase in
more compact winding
arrangements.
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123
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Winding Loss Modeling
Methods to Decrease Winding Losses (3)
Aluminum vs. Copper [13]
Proximity losses are lower in aluminum
conductors over a wide frequency range.
Figure shows a comparison of single round
solid conductors in external field.
d = 0.25 mm
d = 0.50 mm
d = 0.75 mm
d = 1.00 mm
[13]
M. Albach, “Induktive Komponenten in der Leistungselektronik”, VDE Fachtagung - ETG Fachbereich Q1
"Leistungselektronik und Systemintegration", Bad Nauheim, 14.04.2011
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124
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Example
Winding Loss Modeling
Photo & Dimensions
Current Waveform
Demonstration in GeckoMAGNETICS
Material
Grain-oriented steel (M165-35S)
Mittwoch, 4. März 2015
Gecko-Simulations AG
Jonas Mühlethaler
125
APEC 2015
Outline

Magnetic Circuit Modeling

Core Loss Modeling

Winding Loss Modeling

Thermal Modeling

Multi-Objective Optimization

Summary & Conclusion
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126
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Thermal Modeling
Motivation & Model (1)
Ambient
Temperature
Motivation
Thermal modeling is important to …
… avoid overheating.
… improve loss calculation (since the losses
depend on temperature).
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127
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Thermal Modeling
Motivation & Model (2)
Model
Inductor
Transformer
 Determination of thermal resistors is challenging!
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128
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Thermal Modeling
Heat Transfer Mechanisms
Rth 
T
 f (T)
P
Conduction
Independent of temperature T for most materials
Difficult to determine interfaces
between materials
Rth 
T
l

P
A
Convection
Combined effect of conduction and fluid flow

Changes with changing absolute temperature (nonlinear)
Good empirical calculation approach available
Rth 
T
1

P A
Radiation
Small compared to other mechanisms

Modeling the system is demanding
(nonlinear eq. / to describe which components “sees”
the other component).

P  eff A1 (Tb4  Ta4 )

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129
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Thermal Modeling
Thermal Resistance Calculation : (Natural) Convection (1)
Rth 
T
1

P A
 is a coefficient that is influenced by …
… the absolute temperature,
… the fluid property,
… the flow rate of the fluid,
… the dimensions of the considered surface,
… orientation of the considered surface,
… and the surface texture.
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Thermal Modeling
Thermal Resistance Calculation : (Natural) Convection (2)
Empirical solutions known for …
vertical plane
horizontal plane
gap
-top:
- horizontal:
- vertical:
- bottom :
and more …
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Thermal Modeling
Thermal Resistance Calculation : (Natural) Convection (3)
g
l
Structure of Empirical Solutions - Theory

v
gravity of earth: 9.81 m/s2
characteristic length
volumetric thermal expansion coefficient : 1/T (air)
kinematic viscosity: 162.6 ·10-7 m2/s (air)
Name
Measure of …
Nusselt number
Nu
… improvement of heat transfer compared to the case with
hypothetical static fluid.
Grashof number
Gr
… ration between buoyancy and frictional force of fluid.
Prandtl number
Pr
… ratio between viscosity and heat conductivity of fluid.
Pr  0.7 (for air)
Rayleigh number
Ra
… flow condition (laminar or turbulent) of fluid.
Ra  Pr  Gr
l
1 l

 f (Gr, Pr )
A A 
gl 3
Gr  3 T
v
Nu 
 is the heat conductivity of the fluid
air = 25.873 mW/(m K) @ 20C [16]
Procedure

Nu(Gr, Pr )
Nu (Gr, Pr )
l
Rth 
1
A
[16] VDI Heat Atlas, Springer-Verlag, Berlin, 2010
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Thermal Modeling
Thermal Resistance Calculation : (Natural) Convection (4)
Structure of Empirical Solutions - Example
Vertical Plane


Nu  0.825  0.387Ra  f1 Pr 
1/ 6 2
  0.492 
f1  1  
  Pr 

Nu (Gr, Pr )
l
(l = h)
9 / 16 16/ 9




Reference:
[16] VDI Heat Atlas, Springer-Verlag, Berlin, 2010
Tp

Rth 
T
1

P A
Ta
Example
(h = 10 cm, Tp = 60 C, Ta = 20 C, A = h · h)
 Rth = 16.6 K/W
Increase of Winding Surface
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Thermal Modeling
Thermal Resistance Calculation : Conduction
Overview
Normally, with natural
convection it is
Rth,W << Rth,WA
Foil Conductor
Round Conductor
Rth,W is difficult to
determine. One difficulty
is, e.g., to model the
influence of pressure on
the thermal resistance.
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Litz wire shows low
thermal conductivity.
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Example
Thermal Modeling (1)
(1) Horizontal Plane - Top
g
l

v
gravity of earth: 9.81 m/s2
characteristic length : l = a*b / ( 2 ( a+b ) )
volumetric thermal expansion coefficient : 1/T (air)
kinematic viscosity: 162.6 ·10-7 m2/s (air)
gl 3
Gr  3 T
v

Pr  0.7 (for air)
Nu (Gr, Pr )
l
Ra  Pr  Gr
0.766 ( Ra  f 2 ( Pr ))1/5 for Ra  f 2 ( Pr )  7 104
Nu  
1/3
for Ra  f 2 ( Pr )  7 104
0.15 ( Ra  f 2 ( Pr ))
with
  0.322 
f 2  1  
  Pr 

11/20
Mittwoch, 4. März 2015



(turbulent)
Rth 
T
1

P A
Resistor Rth is now
calculated for one
operating point!
( more iterations
are necessary!)
20/11
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(laminar)
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Example
Thermal Modeling (2)
(2) Core to Winding
RCF 
l
K
 1.05
A
W
RW  RWA
Drawing represents the
cross-section of one
coil former side (there
are total 2 x 4 coil
former sides).
Heat flow via
mechanical
attachment has not
been considered.
Quantity Values
Rth,CA  17.4 K/W
Rth,WA  5.8 K/W
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Outline

Magnetic Circuit Modeling

Core Loss Modeling

Winding Loss Modeling

Thermal Modeling

Multi-Objective Optimization

Summary & Conclusion
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Multi-Objective Optimization – Volume vs. Losses
Introduction to the PFC Rectifier
Simplified Schematic
Converter Specifications
Photo of Converter
Goal: Design boost inductor such that the max. current ripple is 4A.
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Multi-Objective Optimization – Volume vs. Losses
Boost Inductor
Photo of Inductor
Selected Inductor Shape
Material
Grain-oriented steel
(M165-35S,
lam. thickness 0.35 mm)
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Multi-Objective Optimization – Volume vs. Losses
Pareto-Optimized Design of Boost Inductor
Simplified Schematic
Boost Inductance
Constraints concerning boost inductors
max. current ripple IHF,pp,max = 4 A
max. temperature Tmax = 120 ºC
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L2,min can be calculated based on the
constraint IHF,pp,max.. The maximum current
ripple IHF,pp,max occurs when the fundamental
current peaks.
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Multi-Objective Optimization – Volume vs. Losses
Pareto-Optimized Design of Boost Inductor - Simplifications
Simplified current / voltage waveforms for optimization procedure
Expectations
Loss overestimation in L2 expected.
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Multi-Objective Optimization – Volume vs. Losses
Pareto-Optimized Design of Boost Inductor - Design Space in GeckoMAGNETICS
Start
LBoost = 2.53 mH
Tmax = 120 ºC
Core
UI 39 – UI 90 cores of DIN41302
Material M165-35S
gap 2.0 … 3.0 mm (by 0.25 mm)
70 – 90 stacked sheets (by 10)
Winding
Solid round wire with fill factor 0.3
Split windings
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Multi-Objective Optimization – Volume vs. Losses
Pareto-Optimized Design of Boost Inductor - Waveform/Cooling in GeckoMAGNETICS
Waveform
Cooling
Forced convection
(-> 3 m/s)
ILF,peak = 21.8 A
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Multi-Objective Optimization – Volume vs. Losses
Pareto-Optimized Design of Boost Inductor - Performing Calculation
Considered effects
Procedure
A reluctance model is introduced to describe the electric /
magnetic interface, i.e. L = f(i).
Air gap stray field
Non-linearity of core material
2)
Core losses are calculated.
DC Bias
Different flux waveforms
Wide range of flux densities
and frequencies
3)
Winding losses are calculated.
4)
Inductor temperature is calculated.
1)
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Skin and proximity effect
Stray field proximity effect
Effect of core to magnetic
field distribution
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Multi-Objective Optimization – Volume vs. Losses
Pareto-Optimized Design of Boost Inductor - Results
Filter Losses vs. Filter Volume
Pareto Front
Prototype built
Pareto-front
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Multi-Objective Optimization – Volume vs. Losses
Detailed Modeling in GeckoMAGNETICS
GeckoCIRCUITS
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GeckoMAGNETICS
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Multi-Objective Optimization – Volume vs. Losses
Results
Photo
Conclusion
Loss modeling very accurate.
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Outline

Magnetic Circuit Modeling

Core Loss Modeling

Winding Loss Modeling

Thermal Modeling

Multi-Objective Optimization

Summary & Conclusion
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Summary & Conclusion
Magnetic Circuit Modeling
Air Gap Reluctance Calculation
Air gap per
unit length
zy-plane
'
zy
R
'
Rzy
y 
lg
0 a
zx-plane
'
zx
R
Results
'
Rzx
x 
lg
0t
Rg   x y
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Jonas Mühlethaler
lg
0 at
149
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Summary & Conclusion
Core Loss Modeling
“The best of both worlds” (Steinmetz & Loss Map approach)
Loss Map
(Loss Material Database)
k , ki ,  ,  ,  r , r , qr ,
T
1
dB
Pv   ki
T 0 dt
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Gecko-Simulations AG

B 
 
n
dt   Qrl Prl
l 1
Jonas Mühlethaler
P
V
150
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Summary & Conclusion
Winding Loss Modeling
Optimal Solid Wire Thickness
Foil vs. Round Conductors
l=1m
10 mm x 0.3 mm
Ipeak = 1 A
PTotal
l=1m
d = 1.95 mm
Ipeak = 1 A
PProx
PSkin
(f = 100 kHz, Ipeak = 1 A, He,peak = 1000 A/m)
Gapped cores: 2D approach
Losses in Litz Wires
l=1m
Internal prox. effect
Skin effect
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Ext. prox. effect
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Summary & Conclusion
Magnetic Design Environment
Magnetics Design Software
GeckoMAGNETICS
Core Material Database
GeckoDB
Circuit Simulator
GeckoCIRCUITS
Automated Measurement System
Prototype
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Jonas Mühlethaler
Verification
(e.g. with Calorimeter)
152
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Summary & Conclusion
Multi-Objective Optimization
PFC Rectifier
Inductor Pareto Front
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GeckoMAGNETICS
Save Time
Fast and accurate design of magnetic components
Easy-to-use for non-expert
Increase Flexibility
Tool shows more than one realization possibility
In-house design of magnetics crucial for optimal designs.
Most Loss Effects are Considered
Skin- and proximity losses in litz, round and foil windings, air gap stray field losses,
DC bias core losses, thermal model, ...
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Additional References
[6]
J. Mühlethaler, J.W. Kolar, and A. Ecklebe, “A Novel Approach for 3D Air Gap Reluctance Calculations”,
in Proc. of the ICPE - ECCE Asia, Jeju, Korea, 2011
[9]
J. Mühlethaler, J. Biela, J.W. Kolar, and A. Ecklebe, “Improved Core Loss Calculation for Magnetic
Components Employed in Power Electronic Systems”, in Proc. of the APEC, Ft. Worth, TX, USA, 2011.
[19]
Jürgen Biela, “Wirbelstromverluste in Wicklungen induktiver Bauelemente”, Part of script to lecture Power
Electronic Systems 1, ETH Zurich, 2007
[20]
J. Mühlethaler, J.W. Kolar, and A. Ecklebe, “Loss Modeling of Inductive Components Employed in
Power Electronic Systems”, in Proc. of the ICPE - ECCE Asia, Jeju, Korea, 2011
[21]
J. Mühlethaler, J. Biela, J.W. Kolar, and A. Ecklebe, “Core Losses under DC Bias Condition based
on Steinmetz Parameters”, in Proc. of the IPEC - ECCE Asia, Sapporo, Japan, 2010.
[22]
B. Cougo, A. Tüysüz, J. Mühlethaler, J.W. Kolar, “Increase of Tape Wound Core Losses Due to
Interlamination Short Circuits and Orthogonal Flux Components”, in Proc. of the IECON, Melbourne, 2011.
[23]
J. Mühlethaler, M. Schweizer, R. Blattmann, J.W. Kolar, and A. Ecklebe, “Optimal Design of LCL Harmonic
Filters for Three-Phase PFC Rectifiers”, in Proc. of the IECON, Melbourne, 2011
Contact
Mittwoch, 4. März 2015
Jonas Mühlethaler
jonas.muehlethaler@gecko-simulations.com
www.gecko-simulations.com
Gecko-Simulations AG
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