by: mark bright and mike donaldson advisor: dr. gary dempsey
Post on 19-Dec-2015
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TRANSCRIPT
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By:Mark Bright
and Mike Donaldson
Advisor:Dr. Gary Dempsey
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Project Goal System Applications Thermal Plant Overview
Engine Side Thermal Side
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The goal of our Engine Control Workstation is to simulate thermal environments that are found in liquid-based cooling systems.
With this system we created several different control methods via MATLAB and Simulink working together to control both the engine and thermal transient and steady state responses.
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Car Application PC Application
The overall goal of this project is to protect the motor with varying loads with minimum energy usage
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Engine Side
Circuitry
Thermal Side
Circuitry
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Engine DSP Board
Thermal
DSP Board
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Generator
Thermistor
Flowmeter
Pump
Pittman
Motor
Cooling Blocks
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Pittman Motor
Tmax = 311 deg F
Thermal impedance 75.9 deg F/watt
(2.9 A)^2 * (3.91 ohm) = 36 watts
36W * (75.9 deg F/watt) = 2732 deg F
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Engine Control:
Minimize C-code and execution time
Learn Auto-Code generation platform of Simulink/DSP interface
Design software for PWM generation and velocity calculation from rotary encoder.
Design closed-loop controllers for velocity and acceleration control.
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32 bit Processor
150 MHz Clock
16 A/D Channels
12 PWM Digital I/O Channels
128K on-chip Flash Memory
9 Ports Total
3.3v Supply
Interfaced to PC by serial port
Inputs and output go through level-shifter IC (5v to 3.3v / 3.3v to 5v)
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User Interaction:Set RPM and
Gain
System Design Simulink Model
MATLAB GUI
Code Composer Auto Code Generated
C Code
TI 2812 DSP Board
PWM Output to Drive Motor
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Both encoder channels from the Pittman motor are offset from each other
Pulses are wired into the DSP board Port 8 – pins 6 and 7
2 counts can be obtained per period for each channel – 4 times as many counts
Allows for Steady State Error of ± 5 RPM
Simulink codes this as inner shaft RPM, which must be converted to outer shaft RPM – 5.9:1 gear ratio
Drag QEP Block into Simulink diagram to implement
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Data sent to GUI is set here
Model is used to generate Code Composer C code
P, PI, and FF Control Implemented
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Data sent to GUI is set here
Model is used to generate Code Composer C code
P, PI, and FF Control Implemented
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Data sent to GUI is set here
Model is used to generate Code Composer C code
P, PI, and FF Control Implemented
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Data sent to GUI is set here
Model is used to generate Code Composer C code
P, PI, and FF Control Implemented
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Data sent to GUI is set here
Model is used to generate Code Composer C code
P, PI, and FF Control Implemented
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Data sent to GUI is set here
Model is used to generate Code Composer C code
P, PI, and FF Control Implemented
Desired RPM
Actual RPM
Controller Output
PWM Duty Cycle
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Simulation model started where the 2008 mini project left off
Bilinear Transform converted analog controllers to digital controllers
P, PI, and FF Control Implemented
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Gp = ______________ (s/146+1)(s/776+1)
______________
(s/146+1)
(s/1460+1)17.1FF=Gp =
17.1 -1
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Simulation: 596 RPM input FF Output is 17 RPM Impulse duration was 2mS
Actual: 596 RPM input FF Output is 17 RPM As expected from
simulation
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100 RPM Step Input
FF Control decreases response time by 20 mS
Less overshoot
Smaller time to first peak
FF Compensation
PI Control Only
RPM vs Time (ms) plot
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Start, Type “guide” in MATLAB
GUI can be designed here with many components
Once designed, MATLAB creates an .m file and .fig file
MATLAB GUI Design
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GUI created in MATLAB and interfaced to Simulink Model
Plots Motor RPM, PWM Duty Cycle, Transient Response, and both PI and Feed Forward Controller Output
User can input desired RPM: 0 to 834 RPM
Optimal controller gains loaded at startup, but user can control both the gain and type of control
GUI updates in real time
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numMsgsOchan1 = r.msgcount('ochan1');
if (numMsgsOchan1)
speed = r.readmsg('ochan1', 'int32');
end
numMsgsOchan2 = r.msgcount('ochan2');
if (numMsgsOchan2)
pid = r.readmsg('ochan2', 'int32');
end
numMsgsOchan3 = r.msgcount('ochan3');
if (numMsgsOchan3)
RPM = r.readmsg('ochan3', 'int32');
end
numMsgsOchan4 = r.msgcount('ochan4');
if (numMsgsOchan4)
PI_Out = r.readmsg('ochan4', 'int32');
end
numMsgsOchan5 = r.msgcount('ochan5');
if (numMsgsOchan5)
FFOut = r.readmsg('ochan5', 'int32');
end
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if ((numMsgsOchan1 ~=0) && (numMsgsOchan2 ~= 0) && (numMsgsOchan3 ~= 0) && (numMsgsOchan4 ~= 0) && (numMsgsOchan5 ~= 0))
axes(handles.axes3);
plot(handles.axes3,x_axis1, RPM);
title(handles.axes3,'Measured speed of the Motor');
xlabel(handles.axes3,'t (s)');
ylabel(handles.axes3,'Speed (RPM)');
grid(handles.axes3,'on');
axis(handles.axes3,[0 5 1 850]);
axes(handles.axes4);
cycle = double(pid);
plot(handles.axes4,x_axis1, cycle);
title(handles.axes4,'Duty Cycle of the PWMWaveform');
xlabel(handles.axes4,'t (s)');
ylabel(handles.axes4,'Duty Cycle (%) ');
grid(handles.axes4,'on');
axis(handles.axes4,[0 5 1 100]);
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Acceleration Control
◦ Adjustable Feed Forward control with different types of input commands: combos of ramps, steps, and parabolic. Load changes can simulate hills and different road conditions.
CAN Bus Interface
◦ Use the DSP board’s CAN bus to send data between the boards. This would allow for a main GUI to control both sides of the system.
Data Logging Feature
◦ Allow for a user to tune controllers and compare results. Could implement a new EE431 / 432 homework or design project around the system.
Set Control Points for Thermal and Engine Response
◦ Set desired temperature for a change in the coolant as well as a engine RPM governor based on load conditions
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Variable Resistance
Anti-aliasing filter
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Use PWM to drive Pump/Fan
Interface from digital to analog
Average Voltage seen by the device
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Opto-Isolator
TIP120 choice
Design for 3A Opto-Isolator
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LPF to ‘DC’ the PWM
Ideal Op Amp theory
Voltage @ Input = Voltage @ Pump
Opto-Isolator
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Conversion of A/D Value to Temperature
Excel Trendline
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Conversion of A/D Value to Temperature
Excel Trendline
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Conversion of A/D Value to Temperature
Excel Trendline
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Conversion of A/D Value to Temperature
Excel Trendline
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Datatype conversions
Function auto-code generated
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Datatype conversions
Function auto-code generated
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Bang – Bang
Improved Bang Bang
P Control
PI Control
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Fan PWM %
Pum
p P
WM
%
0 10 20 30 40 50 60 70 80 90 10060
65
70
75
80
85
90
95
100
-5.5
-5
-4.5
-4
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
Pum
p P
WM
%
Fan PWM%
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Supervisory Control
Further improvement by utilizing Pump and Fan cooling efficiencies
Faster PID Control
Use of more temperature sensors
Use of CAN bus
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Nick Schmidt◦ Case Assembly◦ Hardware Assembly
Dr. Dempsey◦ Case Assembly◦ Hardware Assembly
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Plant Wc is at 899 rad/sec
P Control System Wc was at 164 rad/sec
Gain = .08
Phase Margin with P control:◦ 115
Gp = __________________ (s/146+1)(s/776+1)
17.1
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Gp(s) =K * 1/(Tc(s)+1) * e^-(s)Td
Pump/Plant ◦ K = (-.8 degrees F / 6.4 V)◦ Tc = 20◦ Td = 6
Fan/Plant◦ K = (-9.6 degrees F / 13V)◦ Tc = 12◦ Td = 15
Thermal Transfer Functions
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Control Toolbox Results P-Pump
◦ Wc = .148 radians PM = 105 GM =22.1dB
P-Fan◦ Wc = ? PM = undefined GM =29.4dB
PI-Pump◦ Wc = .39 radians PM = -139 GM =16.1dB
P-Pump◦ Wc = .0966 radians PM = -48 GM =-15.92dB
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OCHAN’s allow for data to be outputted to:◦ GUI◦ Workspace
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PWM Brush Type Servo Amplifer – Model 10A8DD
Protected for over-voltage and over-current
DC Supply Voltage: 20-80v
Peak Current: ±10A Maximum Continuous
Current: ±6A
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