The document describes a simulation of a PMSM motor control system for electric power steering controllers. It includes:
1) A system block diagram showing the main components of an EPS system including a PMSM motor, steering mechanism, and EPS control unit.
2) Simulink models of the key system elements - the PMSM motor, position sensor, current sensing, PI controller, and inverse Park and space vector modulation models.
3) Simulation and experimental results showing the effects of position sensor resolution and current sensing errors on torque ripple, and validating the simulated d-axis step response with experimental measurements.
4) A conclusion that the complete PMSM drive model and experimental validation can
4 matched filters and ambiguity functions for radar signals-2Solo Hermelin
Matched filters (Part 2of 2) maximizes the output signal-to-noise ratio for a known radar signal at a predefined time.
For comments please contact me at solo.hermelin@gmail.com.
For more presentations on different subjects visit my website at http://www.solohermelin.com.
4 matched filters and ambiguity functions for radar signals-2Solo Hermelin
Matched filters (Part 2of 2) maximizes the output signal-to-noise ratio for a known radar signal at a predefined time.
For comments please contact me at solo.hermelin@gmail.com.
For more presentations on different subjects visit my website at http://www.solohermelin.com.
I am Martin J. I am a Signal Processing Assignment Expert at matlabassignmentexperts.com. I hold a Master's in Matlab, University of Maryland. I have been helping students with their assignments for the past 10 years. I solve assignments related to Signal Processing.
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I am Walter G. I am a Signal Processing Assignment Expert at matlabassignmentexperts.com. I hold a Master's in Matlab, Oxford University, UK. I have been helping students with their assignments for the past 7 years. I solve assignments related to Signal Processing.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Signal Processing Assignment.
Presentation on Fourier Series
contents are:-
Euler’s Formula
Functions having point of discontinuity
Change of interval
Even and Odd functions
Half Range series
Harmonic analysis
I am Martin J. I am a Signal Processing Assignment Expert at matlabassignmentexperts.com. I hold a Master's in Matlab, University of Maryland. I have been helping students with their assignments for the past 10 years. I solve assignments related to Signal Processing.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Signal Processing Assignment.
I am Walter G. I am a Signal Processing Assignment Expert at matlabassignmentexperts.com. I hold a Master's in Matlab, Oxford University, UK. I have been helping students with their assignments for the past 7 years. I solve assignments related to Signal Processing.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Signal Processing Assignment.
Presentation on Fourier Series
contents are:-
Euler’s Formula
Functions having point of discontinuity
Change of interval
Even and Odd functions
Half Range series
Harmonic analysis
We have implemented a multiple precision ODE solver based on high-order fully implicit Runge-Kutta(IRK) methods. This ODE solver uses any order Gauss type formulas, and can be accelerated by using (1) MPFR as multiple precision floating-point arithmetic library, (2) real tridiagonalization supported in SPARK3, of linear equations to be solved in simplified Newton method as inner iteration, (3) mixed precision iterative refinement method\cite{mixed_prec_iterative_ref}, (4) parallelization with OpenMP, and (5) embedded formulas for IRK methods. In this talk, we describe the reason why we adopt such accelerations, and show the efficiency of the ODE solver through numerical experiments such as Kuramoto-Sivashinsky equation.
7. 3. SIMULINK MODELS OF SYSTEM ELEMENTS
3. SIMULINK MODELS OF
SYSTEM ELEMENTS
7
8. 3. SIMULINK MODELS OF SYSTEM ELEMENTS
Permanent Magnet Synchronous Motor (PMSM) Model
8
9. 3. SIMULINK MODELS OF SYSTEM ELEMENTS
Permanent Magnet Synchronous Motor (PMSM) Equations
Park transformation equations D-Q axis electric circuit equations
2π 4π
2
vd = [va cos θ + vb cos(θ −
3 3
) + vc cos(θ −
3
)] vd = Rs id + Ld d
i − Lqω e dt iq
dt d
d
2π 4π
2
vq = [−va sin θ − vb sin s (θ −
3 3
) − vc sin(θ −
3
)] vq = Rs iq + Lq dt iq + Ldω e dt id + ω e λPM
d d
Inverse Park transformation equations
Torque equations
ia = id cosθ − iq sin θ
3
Te = P[λ PM iq + ( Ld − Lq )id iq ] 2π 2π
2 ib = id cos(θ − ) − iq sin(θ − )
3 3
d
Te = TL + K f ω m + J ωm 4π 4π
dt ic = id cos(θ − ) − iq sin(θ − )
3 3
9
10. 3. SIMULINK MODELS OF SYSTEM ELEMENTS
Motor Position Sensor Model
Complete Sensor:
Error generator:
10
11. 3. SIMULINK MODELS OF SYSTEM ELEMENTS
Current Sensing Model
V_B
(1) V1
(5) (3)
Vαβ
V_A
V3 V2
(4) (6) (2)
V_C
11
18. 4. SIMULATION & EXPERIMENTAL RESULTS
Measured torque ripple with 48-count resolution
Phase A current is 10A/div. Average torque = 1.05 N.m.
Torque ripple = 0.023 N.m. (peak to peak)
18
19. 4. SIMULATION & EXPERIMENTAL RESULTS
Simulated current sensing with 0.15A error
3-per-rev torque ripple is about 0.017 N.m
Current sense error = 0.15 (A)
0.465
0.46
Torque(N.m.)
0.455
0.45
0.445
0.44
0.435
0.5 1 1.5 2 2.5 3 3.5 4
Time (Sec.)
15
10
Motor current (A)
5
0
-5
-10
-15
0 0.5 1 1.5 2 2.5 3 3.5 4
Time (Sec.)
19
20. 4. SIMULATION & EXPERIMENTAL RESULTS
Measured torque ripple with current sense error
3-per-rev torque ripple is about 0.020 N.m
Phase A current is 10A/div.
20
21. 4. SIMULATION & EXPERIMENTAL RESULTS
Measured torque ripple with current error eliminated
3-per-rev torque ripple is eliminated
Phase A current is 10A/div.
21
22. 4. SIMULATION & EXPERIMENTAL RESULTS
Simulated d-axis step response
Rise time is about 2 ms.
There is no overshoot.
22
23. 4. SIMULATION & EXPERIMENTAL RESULTS
Measured d-axis step response
Rise time is 1.8 ms.
There is no overshoot.
23
24. 5. CONCLUSION
CONCLUSION
• A complete PMSM drive model has been
presented.
• Experimental results are provided to validate the
simulation models.
• The effect of position sensor resolution and
current measurement errors are simulated and
validated.
• The current loop step response is simulated and
validated.
• The simulation work helps reduce product cost
and development time.
24