development of a neuro fuzzy technique for position sensor elimination in a srm l. o. henriques,...
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![Page 1: Development of a Neuro Fuzzy Technique for Position Sensor Elimination in a SRM L. O. Henriques, L.G. Rolim, W. I. Suemitsu, P.J. Costa Branco](https://reader031.vdocuments.net/reader031/viewer/2022032201/56649d405503460f94a1a022/html5/thumbnails/1.jpg)
Development of a Neuro Fuzzy Technique for Position Sensor Elimination in a SRM
L. O. Henriques, L.G. Rolim, W. I. Suemitsu,
P.J. Costa Branco
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Presentation
• Introduction
– Operating modes
• System Training and Operation– Estimator types
• Results– Simulated and experimental
• Conclusions
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Introduction
• Necessity for a perfect operation:– Correct excitation of the phases in synchronism with
the rotor position
• Reasons to remove the position sensor:– Cost, reliability, size, weight and inertia
• Basic voltage equation:
n
kkjjj dt
dRiv
1
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Operating Modes in Sensorless Control
ba s e
5- Veryh igh speed
4- H ighspeed
3- Lowspeed
2- Very lowspeed
1- S till
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Operating Modes in Sensorless Control
•Region 1 and 2: – Counter EMF is smaller than the DC bus voltage.
– Can operate in CR-PWM (hysteresis)
–Drawback: produces significant braking torque
–Voltage pulse injection to measure the inductance
base
5- Veryhigh speed
4- Highspeed
3- Lowspeed
2- Very lowspeed
1- Still
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Operating Modes in Sensorless Control
•Region 3– Limitations (precision and accurancy) using diagnosis signal techniques
•Region 4– Operation is single pulse
– Region named “Constant power region”
•Region 5– Requires efficient real time algorithms
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System Training and Operation
• Conventional estimator
dt
di
iiRv
dt
d...
1
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System Training and Operation
• Initial proposed estimator
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Voltage Profile Training Data
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 -150
-100
-50
0
50
100
150
Voltage (V)
-8
-6
-4
-2
0
2
4
Filtered Voltage
(V)
time (s) 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
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System Training and Operation
• Final proposed estimator
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sensor
+
-
Training phase
1/s
Operation phase
Training and Operation Phase
PIController
+
+
Converter+
Motor+
-
NeuroFuzzy
Compensator
NeuroFuzzy
Estimator
filter
Vphases
iref
iref
ipi
i
re f
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Simulated Result
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
10
20
30
40
50
60
70
80
90
Time(s)
Po
siti
on
(deg
ree)
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
10
20
30
40
50
60
70
Time(s)
spee
d(r
pm
)
estimated real
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Experimental Results
0 500 1000 1500-5
0
5 Filtered Phase Voltage
phas
e 1
(vol
t)
0 500 1000 1500-5
0
5
0 500 1000 1500-5
0
5
Sample point #
phas
e 2
(vol
t)ph
ase
3(v
olt)
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Experimental Result
0 500 1000 15000
0.5
1
1.5
2Reference current
Sample point #
Am
pere
(A
)
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Experimental Result
0 100 200 300 400 50090
95
100
105
110Real Speed
Sample point #
(rpm
)
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Experimental Result
Estimated Speed
0 100 200 300 400 50085
90
95
100
105
110
Sample point #
(rpm
)
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Experimental Result
0 100 200 300 400 50085
90
95
100
105
110Real and Estimated Speed
Sample point #
(rpm
)
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Conclusions
• A review of the torque-speed operating modes is shown
• A new technique of position sensor elimination is presented, based on intelligent techniques with neural nets and fuzzy logic
• Simulated and experimental results demonstrated the feasibility of the technique.
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Basic Voltage Equation
n
k
kjdt
djRijv
1
dt
di.
idt
d.jRijv
dt
di.
idt
d.
dt
d)i,(f
dt
di.
ii.Rv.
dt
d 1