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Transcript of Magnetic Components in Electric Circuits Understanding thermal behaviour and stress Peter R. Wilson,...
Magnetic Components in Electric Circuits
Understanding thermal behaviour and stress
Peter R. Wilson, University of Southampton
2School of Electronics and Computer Science, University of Southampton, UK
What are we trying to understand?
How are Magnetic Materials Affected by Temperature?
What is the impact on Magnetic Components?
How does this affect electric circuit behaviour?
-0.4-0.3-0.2-0.1
00.10.20.30.40.5
-150 -100 -50 0 50 100 150H (A/m)
B (T
)
T=27 T=95 T=154
3School of Electronics and Computer Science, University of Southampton, UK
Magnetic Material Characteristics
Ferrous Magnetic Materials exhibit hysteresis The magnetization of the material is partly reversible (no
loss) and partly irreversible (loss)
M
H
TotalMagnetization
(Stored Energy)
ReversibleMagnetization
Happlied
IrreversibleMagnetization(Lost Energy)
4School of Electronics and Computer Science, University of Southampton, UK
Energy Lost in Magnetic Materials
The Material will therefore dissipate energy as heat under heavy loading:
B (T)
H (At/m)
dB
BH CurveAnhysteretic Fn.
RecoveredEnergy
DissipatedEnergy
5School of Electronics and Computer Science, University of Southampton, UK
The effect of environmental Temperature?
How does the overall temperature of the material affect its behaviour? Eventually the Curie point is reached and the material
ceases to have any effective permeability
-0.4-0.3-0.2-0.1
00.10.20.30.40.5
-150 -100 -50 0 50 100 150H (A/m)
B (
T)
T=27 T=95 T=154
Data for a 3F3 Material, 10mm Toroid obtained by the author, measured using a Griffin-Grundy oven to control the temperature
6School of Electronics and Computer Science, University of Southampton, UK
Modeling Magnetic Materials
Modeling Magnetic Materials is particularly complex, with several choices Jiles Atherton, Preisach, Hodgdon, et al
The Jiles Atherton model is often used in circuit simulators:
+
+M
H e
M r e v
M i r r
M a n
H
a
aH
)/tanh(
1
c
c
1
H
c1
1
sM
)( MMk
MM
an
an
AHMM S /*0 B
7School of Electronics and Computer Science, University of Southampton, UK
Jiles Atherton Model
The results are particularly good at predicting the BH loop behaviour in ferrites, however the Preisach model is often better for “square” loop materials
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
-150 -100 -50 0 50 100 150
H (At/m)
B (
T)
Measured Simulated
8School of Electronics and Computer Science, University of Southampton, UK
Building a Magnetic Component
To build a component (e.g. inductor) for electric circuits, we need both a core model and a winding:
MagneticDomain
ElectricalDomain
dt
dnv p
pp
F=
pppinmmf *=
pF
pi
CorecF
cmmf
9School of Electronics and Computer Science, University of Southampton, UK
Adding the Thermal Dependence
To add dynamic thermal behaviour, use a network to effectively model the thermal aspects of the material and the environment
Jiles-AthertonNon-LinearCore Model
H B
DefaultModelParameters
Modified ModelParameters
ThermalNetwork
T(°C)
Power
ParameterFunctions
WindingLossCurrent
Power
EddyCurrent
Loss
Power
10School of Electronics and Computer Science, University of Southampton, UK
Thermal Network Modeling
We have choices to make regarding the thermal network, in particular a distributed or lumped model In most cases a lumped model is perfectly adequate
Hysteresis+ Eddy Current
+ WindingPower Loss
Convection
Cth - Core
Tsurface
Tair
AmbientTemperature
Emission
11School of Electronics and Computer Science, University of Southampton, UK
Characterize the Magnetic Material
It is a relatively simple matter to characterize the magnetic material model by measuring its behaviour and calculating the resulting model parameters
Np
Ri
Ns
CH1
CH2
PowerAmplifier
DS345Signal
Generator
TektronixTDS220DigitalOscilloscope
Griffin-Grundy OvenRS 206-3750Temperature
Meter TN10 - 3F3
30.00
32.00
34.00
36.00
38.00
40.00
42.00
0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0
Temperature (Degrees Celsius)A
(-)
A(Measured) A(Second Order Fit)
12School of Electronics and Computer Science, University of Southampton, UK
Building a Circuit Model…
Using the characterized thermally dependent model of the core, winding models and a thermal network, we can make the electric circuit model (in this case a transformer) dynamically affected by temperature
MMF
winding_th5
2
1 3
4
expja_th63
1 2
V127+
-
vp
I2
R310
MMF
emission
5
2
13
4
U2
R41k
winding_th
U1 U3
rconv
R11G ctherm
tair
tcore
1
2
2
1
1
2
PARAMETERS___Area 293uCth 0.07D 3.8e-3
PARAMETERS___C 700Dens 4750Vol 188n
U6
U4
U5
13School of Electronics and Computer Science, University of Southampton, UK
Results of Dynamic Thermal behaviour
At ambient Temperatures, the model behaves very closely to the measured data
-0.1-0.08-0.06-0.04-0.02
00.020.040.060.080.1
0 0.005 0.01 0.015 0.02 0.025
Time (s)
Vo
ltag
e (V
)
Measured Simulated
14School of Electronics and Computer Science, University of Southampton, UK
Results of Dynamic Thermal behaviour
At increased temperatures, the transformer output voltage drops due to reduced permeability
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0 0.005 0.01 0.015 0.02 0.025
Time (s)
Vo
ltag
e (V
)
Measured Simulated
15School of Electronics and Computer Science, University of Southampton, UK
Dynamic Magnetic and thermal behaviour
The Flux Density decreases as the magnetic core temperature increases
-0.4-0.3-0.2-0.1
00.10.20.30.4
0 0.05 0.1 0.15 0.2
Time (s)
B (
T)
B
0
10
20
30
40
50
60
70
0 0.02 0.04 0.06 0.08 0.1
Time (s)
Co
re S
urf
ace
Tem
per
atu
re
(Deg
rees
C)
tcore
16School of Electronics and Computer Science, University of Southampton, UK
Conclusions
The magnetic material can be modelled to reflect not only the complex BH curve, but also its dependence on temperature
The temperature can be introduced dynamically to the magnetic material model
The component can be modelled using a thermal network to accurately predict the dynamic thermal behaviour
A complete electric circuit can be simulated that includes dynamic thermally dependent magnetic component and accurately predicts its behaviour
17School of Electronics and Computer Science, University of Southampton, UK
References
1. Wilson, P. R., Ross, J. N. and Brown, A. D. “Magnetic Material Model Optimization and Characterization Software”. In: Compumag, 2001
2. Wilson, P. R., Ross, J. N. and Brown, A. D. “Dynamic Electrical-Magnetic-Thermal Simulation of Magnetic Components”. In: IEEE Workshop on Computers in Power Electronics, COMPEL 2000
3. P.R. Wilson, J.N Ross & A.D. Brown, “Predicting total harmonic distortion in asymmetric digital subscriber line transformers by simulation”, IEEE Transactions on Magnetics, Vol. 40 , Issue: 3 , 2004, pp. 1542–1549
4. P.R. Wilson, J.N Ross & A.D. Brown, “Modeling frequency-dependent losses in ferrite cores”, IEEE Transactions on Magnetics ,Vol. 40 , No. 3 , 2004, pp. 1537–1541
5. P.R. Wilson, J.N Ross & A.D. Brown, “Magnetic Material Model Characterization and Optimization Software”, IEEE Transactions on Magnetics, Vol. 38, No. 2, Part 1, 2002, pp. 1049-1052
6. P.R. Wilson, J.N Ross & A.D. Brown, "Simulation of Magnetic Component Models in Electric Circuits including Dynamic Thermal Effects", IEEE Transactions on Power Electronics, Vol. 17, No. 1, 2002, pp. 55-65
7. P.R. Wilson & J.N Ross, "Definition and Application of Magnetic Material Metrics in Modeling and Optimization", IEEE Transactions on Magnetics, Vol. 37, No. 5, 2001, pp. 3774-3780
8. P.R. Wilson, J.N Ross & A.D. Brown, "Optimizing the Jiles-Atherton model of hysteresis using a Genetic Algorithm", IEEE Transactions on Magnetics, Vol. 37, No. 2, 2001, pp. 989-993