The document discusses simulating a magnetic angle measurement system using ANSYS and MATLAB/Simulink. It describes modeling the magnetic circuit of a permanent magnet and pole wheels using ANSYS, exporting the flux density results, and incorporating them into a Simulink model of a GMR sensor and signal conditioning circuit. The goals are to analyze error sources, optimize the design, and test sensor calibration techniques.

1. Simulation of a magnetic angle
measurement system
ANSYS Conference & 7. CADFEM Austria User‘s Meeting 26. – 27. April 2012
Gernot Binder

2. Outline
 Problem description
 Electrically commutated motor working principle
 Sinusoidal commutation
 Sinusoidal commutation using GMR angle sensor
 Out of axis angle measurement
 Magnetic circuit simulations
 Diametrically magnetized ring magnet
 Pole wheels with different number of pole pairs
 Nonius principle
 System simulations
 Incorporating FEM results in the MATLAB Simulink model
 Sensor Calibration
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3. EC motor working principle
 Three excitation coils on stator
 Diametrically magnetized permanent
magnet on rotor
 No mechanical contact between stator
and rotor  brushless
 Benefits
¬ No mechanical wear
¬ small rotor inertia
 Drawbacks
¬ Need for a rotor/shaft position
feedback system for current
commutation
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4. Sinusoidal commutation
 Three energized phases at a time
 Benefits of sinusoidal commutation:
 Low torque ripple
 high efficiency
 Rotor position has to be known with high accuracy
3 excitation currents shifted by 120°
1,2
1
0,8
0,6
Phase current
0,4
0,2
0 U
-0,2
-0,4 V
-0,6
-0,8 W
-1
-1,2
0 100 200 300
reference angle
Principle of a 3-phase driver stage and corresponding phase currents
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5. Sinusoidal commutation using GMR-based sensor
 Diametrically magnetized permanent magnet at the end of shaft
 GMR-based angle sensor placed in front of the shaft
¬ Two Wheatstone bridges oriented at 90° deliver sine and cosine
signals. Angle is given by arc tangent of signal amplitude relation
 Benefits
¬ High resolution allows smooth torque control
¬ Only one angle sensor instead of three Hall switches required
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6. GMR-effect
 Giant Magneto Resistive effect
 Spin Valve Stack
¬ Two ferromagnetic layers divided by non-magnetic spacer layer
¬ Magnetization of free layer follows external magnetic field
¬ Resistance in spacer layer depends on magnetization
orientation of the magnetic layers
R R (1  cos m1m 2 )
(m1m 2 )  ( )GMR 
R R 2
AAF
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7. Out of axis measurement
 End of shaft measurement not always possible
 Place sensor out of axis at the shaft circumference
 Problems occur:
 Angle accuracy depends on:
¬ Number of pole pairs / Magnetic coding
¬ Shaft diameter
¬ Sensor distance
 Use ANSYS to design a magnetic circuit that delivers
appropriate magnetic fields
 Use Matlab/Simulink for a combined system simulation
(Magnetic circuit – GMR sensor – Integrated signal
conditioning)
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8. Error sources
ANSYS Matlab / Simulink
Geometry Offsets
Structure Phase shifts
Magnetization Amplitudes
Sensor location Temperature drifts
Error compensation
Overall angle error
Magnetic
Sensor
circuit
related
related
errors
errors
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9. Magnetic analysis 90
0.02
120 60 400
0.02
measured angle °
Bx 0.015 300
0.015 By
0.01 200
150 30
0.01
100
magnetic flux density in T
0.005
0.005
0
0 50 100 150 200 250 300 350 400
0 180 0 reference angle °
0.1
-0.005
0.05
angle error °
-0.01
210 330 0
-0.015
-0.05
-0.02 240 300 -0.1
0 50 100 150 200 250 300 350 400 0 50 100 150 200 250 300 350 400
reference angle in ° 270 reference angle °
90
0.04
0.04
120 60
400
0.03 0.03 single pole wheel 2 poles
0.02 150 0.02 30 200
magnetic flux density in T
0.01 0.01
0
0 0 50 100 150 200 250 300 350 400
180 0
-0.01 50
angle error °
-0.02
210 330 0
-0.03
-0.04 -50
0 50 100 150 200 250 300 350 400 240 300 0 50 100 150 200 250 300 350 400
reference angle in °
270 reference angle °
90
0.04
0.04
120 60 400
Bx
0.03 By 0.03 single pole wheel 2 poles
0.02 150 0.02 30 200
magnetic flux density in T
0.01 0.01
0
0 50 100 150 200 250 300 350 400
0
180 0
50
-0.01
angle error °
-0.02
0
210 330
-0.03
-50
-0.04 240 300 0 50 100 150 200 250 300 350 400
0 50 100 150 200 250 300 350 400
reference angle in °
reference angle °
270
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10. Nonius principle
 By increasing the number of pole pairs,
400
single pole wheel 2 poles
the error can be reduced
200
0
0 50 100 150 200 250 300 350 400
 But measured angle is ambiguous 50
angle error °
over one shaft revolution 0
-50
0 50 100 150 200 250 300 350 400
reference angle °
 By the Nonius principle unambiguity of
angle over one shaft revolution is
achieved
 2 Sensors triggered by 2 pole wheels
¬ 1st pole wheel has x pole pairs
¬ 2nd pole wheel has x+1 pole pairs
 Output angle is calculated by
subtracting the low-res angle of sensor
1 from the high-res angle of sensor 2
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11. Result of the Nonius principle
 Maximum angle error is about +/- 0.07° (ideal magnetization)
400
measured angle °
300
200
40 poles
100 38 poles
output angle
0
0 50 100 150 200 250 300 350 400
reference angle °
0.1
angle error
0.05
angle error °
0
-0.05
-0.1
0 50 100 150 200 250 300 350 400
reference angle °
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12. Design optimization
 How large is the influence of non-ideal magnetization?
 Non-ideal magnetization: slightly varying pole widths
¬ Production related alternating width of adjacent poles (+/- 2.2 %)
 Error increases to +/- 0.16°
400
measured angle °
300
200
40 poles
100 38 poles
output angle
0
0 50 100 150 200 250 300 350 400
reference angle °
0.2
angle error
0.1
angle error °
0
-0.1
-0.2
0 50 100 150 200 250 300 350 400
reference angle °
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13. MATLAB Simulink model
 Influence of sensor electronics and signal processing is modeled
using MATLAB Simulink
 B-field components obtained from FEM simulations are exported
as *.txt-file
Magnetic Circuit Sensor Related Errors Overall
Related Errors Angle Error
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14. Incorporating FEM results
 Reference angle of shaft  Model of the Wheatstone
serves as index for the bridge
LUT
 Angle is decomposed in
 From the entries in the sine and cosine component
LUT the angle of the
 Output voltages vary in
magnetic field is
amplitude, phase and
calculated by the arc
offset
tangent function
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15. Sensor calibration techniques
 Dedicated algorithm implemented in the signal conditioning
circuit to compensate for offsets, amplitudes, phase shifts and
temperature drifts.
Angle performance without Angle performance with
parameter correction parameter correction
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16. Results before and after sensor calibration
Output signals of GMR sensor
without compensation measured angle angle error
0.08 deviation from reference angle
400
Vx 60
measured angle without parameter correction Simulink model
Vy
0.06 350
40
300
0.04
250 20
measured angle in °
Amplitude in V
0.02
Error in °
200
0
0 150
-20
100
-0.02
50 -40
-0.04
0
-60
-0.06 -50 0 0.5 1 1.5 2 2.5 3 3.5
0 0.5 1 1.5 2 2.5 3 3.5 4 0 0.5 1 1.5 2 2.5 3 3.5 4 -3
time in seconds -3 time in seconds -3 x 10
x 10 x 10
Output signals after parameter correction
4 measured angle angle error
x 10
2 deviation from reference angle
400 0.06
measured angle after parameter correction Simulink model
1.5
350 0.04
1
300 0.02
measured angle in °
Amplitude in digits
0.5
250 0
Error in °
0 200 -0.02
-0.5 150 -0.04
-1 100 -0.06
-1.5 50 -0.08
-2 -0.1
0 0 0.5 1 1.5 2 2.5 3 3.5 4
0 0.5 1 1.5 2 2.5 3 3.5 4 0 0.5 1 1.5 2 2.5 3 3.5 4
-3
time in seconds -3 time in seconds -3 x 10
x 10 x 10
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17. Thank you for your attention!
 References
 Infineon Technologies AG. Position Feedback for Motor Control Using Magnetic Sensors. Infineon
Technologies AG, 2010.
 Infineon Technologies AG. TLE5012B GMR-Based Angular Sensor - Datasheet. Infineon Technologies
AG, 2010.
 Infineon Technologies AG. TLE5009 GMR-Based Angular Sensor - Application Note TLE5009
Calibration. Infineon Technologies AG, 2010.
Copyright © Infineon Technologies 2012. All rights reserved. Page 17

18. Appendix

19. Process for obtaining simulation results (1)
 Ansys DesignModeler
 Definition of:
¬ geometry of pole wheel
¬ coordinate systems for magnetization
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20. Process for obtaining simulation results (2)
 Ansys Mechanical
 Definition of
¬ Materials
¬ Magnetization direction
 Creating user defined results
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21. Exporting results as LUT
Bx
By
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23. Fragen? Interesse?
Kontaktieren Sie uns – wir helfen Ihnen gerne!
CADFEM (Austria) GmbH
Wagenseilgasse 14
1120 Wien
Tel. +43 (0)1 587 70 73 – 0
E-Mail. info@cadfem.at
Web. http://www.cadfem.at
Immer aktuell informiert – CADFEM Blog, Xing und Youtube-
Channel
CADFEM Blog - Umfassend informiert
• News zur FEM-Simulation - What‘s hot? What‘s new?
• Video-Tutorials - ANSYS, LS DYNA & mehr
• Hinter den Kulissen: CADFEM intern
CADFEM Youtube Channel - Tips & Trick
• Video Tutorials - ANSYS Software und CADFEM Applications
CADFEM auf Xing - News kompakt
• Vorschau auf Events & Seminare
• Neue CADFEM Produkte
• CADFEM Jobbörse

24. Fragen? Interesse?
Kontaktieren Sie uns – wir helfen Ihnen gerne!
CADFEM (Austria) GmbH
Wagenseilgasse 14
1120 Wien
Tel. +43 (0)1 587 70 73 – 0
E-Mail. info@cadfem.at
Web. http://www.cadfem.at
Immer aktuell informiert – CADFEM Blog, Xing und Youtube-Channel
CADFEM Blog - Umfassend informiert
• News zur FEM-Simulation - What‘s hot? What‘s new?
• Video-Tutorials - ANSYS, LS DYNA & mehr
• Hinter den Kulissen: CADFEM intern
CADFEM Youtube Channel - Tips & Trick
• Video Tutorials - ANSYS Software und CADFEM Applications
CADFEM auf Xing - News kompakt
• Vorschau auf Events & Seminare
• Neue CADFEM Produkte
• CADFEM Jobbörse