Modeling and Optimization of Trajectory-based Combustion ... · Abhinav Tripathi, Prof Zongxuan Sun...
Transcript of Modeling and Optimization of Trajectory-based Combustion ... · Abhinav Tripathi, Prof Zongxuan Sun...
Abhinav Tripathi, Prof Zongxuan Sun
Abhinav TripathiProfessor Zongxuan Sun
Department of Mechanical EngineeringUniversity of Minnesota
Modeling and Optimization of Trajectory-based Combustion Control
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Abhinav Tripathi, Prof Zongxuan Sun
Presentation Outline
• Motivation, Background and Objective
• Trajectory based Combustion Control
– Previous Work: Modeling and Optimization Framework
• Approach for experimental validation– Simplified Problem: Combustion Phasing Control
– Hardware-in-loop Framework using CT-RCEM
– Experimental Results
• Conclusions
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Abhinav Tripathi, Prof Zongxuan Sun
Low Temperature Combustion (LTC) modes are kinetically modulated
Extremely fuel-lean operation leading to high fuel efficiency
High CR operation and faster heat release leading to higher fuel
efficiency
Low peak temperature leading to lower NOx
Background – Advanced Combustion Modes
Fuel efficiency
Emis
sion
per
form
ance
Spark Ignition Engine
DieselEngine
LTCEngine
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Global trend - tighter regulations for fuel efficiency and emissions
Abhinav Tripathi, Prof Zongxuan Sun
Background – HCCI Combustion
• HCCI is a kinetically modulated combustion mode
• Relies on thermodynamic conditions (P,T) for autoignition instead of external input unlike SI and CI
• Existing control methods include
Exhaust gas recirculation (EGR)
Varying valve timing and
Charge stratification
• Control input is provided at a single time instant during the cycle
HCCI Combustion Process
Chemical Kinetics of fuel
In-cylinder Gas Dynamics
Thermal heat releaseReaction productionReaction rate
PressureTemperatureSpecies concentration
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Highly non-linear and coupled dynamics
Is there a better way to modulate the in-cylinder dynamics?
Abhinav Tripathi, Prof Zongxuan Sun
No mechanical crankshaft
Opposed Piston Opposed Cylinder Engine
Direct Fuel Injection
Background – FPE at UMN
Piston trajectory not constrained by mechanical crankshaft
Variable compression ratio and variable piston trajectory shape
•Advanced combustion strategies
•Multi-fuel operation
Reduced frictional losses
Faster response time
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Exhaust Ports
Intake Ports
IntakePorts
ExhaustPorts
Check Valves
Servo Valve
On-off Valve
On-off Valve
LP
HPOuter Piston Pair
Inner Piston Pair
Hydraulic Chambers
Virtual crankshaft mechanism enables the
FPE pistons to precisely track the
prescribed piston trajectory
Abhinav Tripathi, Prof Zongxuan Sun
Presentation Outline
• Motivation, Background and Objective
• Trajectory based Combustion Control
– Previous Work: Modeling and Optimization Framework
• Approach for experimental validation– Simplified Problem: Combustion Phasing Control
– Hardware-in-loop Framework using CT-RCEM
– Experimental Results
• Conclusions
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Abhinav Tripathi, Prof Zongxuan Sun
Chemical Kinetics of Fuel
In-cylinder Gas Dynamics
Thermal heat releaseReaction productReaction ratePressureTemperatureSpecies concentration
Variable Piston Trajectories
Virtual Crankshaft Mechanism
Volume
What is Trajectory-based Combustion Control
Use complete piston trajectory as control input to modulate
in-cylinder gas dynamics
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Free Piston Engine
Abhinav Tripathi, Prof Zongxuan Sun
Inner Loop: piston motion control - virtual crankshaft
Outer Loop: Trajectory-based combustion control
Basic Framework - Trajectory-based Combustion Control
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Find piston trajectory which minimizes emissions & maximizes work output
Control
signalsSupervisory Control Virtual
Crankshaft
In-cylinder pressure
Optimal piston
trajectory
Piston position
Inner-loop: Active Motion Control
Outer-loop: Trajectory Optimization
Operating
point
Output
power
Combustion Analyzer
Abhinav Tripathi, Prof Zongxuan Sun
Presentation Outline
• Motivation, Background and Objective
• Trajectory based Combustion Control
– Previous Work: Modeling and Optimization Framework
• Approach for experimental validation– Simplified Problem: Combustion Phasing Control
– Hardware-in-loop Framework using CT-RCEM
– Experimental Results
• Conclusions
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Abhinav Tripathi, Prof Zongxuan Sun
Experimental Validation – Simplified Problem
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Control Objective: Attain optimal combustion phasingby changing the piston trajectory
• Combustion phasing determined in terms of Location of Peak Pressure (LPP)
• Piston trajectory characterized in terms of shape parameter (Ω)
• Desired LPP (Λ𝑑𝑑𝑑𝑑𝑑𝑑) is the optimal LPP determined offline through simulation
• Supervisory control determines the trajectory input based on the error in combustion phasing
• Active motion control ensures that the FPE operates on the trajectory determined by supervisory control
Supervisory Control
Combustion Analysis
Λ𝑑𝑑𝑑𝑑𝑑𝑑 +
-
Λ𝑖𝑖
𝑒𝑒𝑖𝑖 Ω𝑖𝑖+1
𝑥𝑥(𝑡𝑡)
𝑃𝑃(𝑡𝑡)
Virtual Crankshaft FPE
Abhinav Tripathi, Prof Zongxuan Sun
Hardware-in-loop Setup Using CT-RCEM
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Control Objective: Attain optimal combustion phasing by changing the piston trajectory • CT-RCEM used to obtain combustion data
• Extremely precise control over initial and boundary conditions
• Ability to perform cycle based chemical kinetics analysis for NOx, HC, CO studies as required
• For this study, offline iterative learning control used as supervisory control
Iterative Learning Control
Combustion Analysis
Λ𝑑𝑑𝑑𝑑𝑑𝑑 +
-Λ𝑖𝑖
𝑒𝑒𝑖𝑖 Ω𝑖𝑖+1
𝑥𝑥(𝑡𝑡)
𝑃𝑃(𝑡𝑡)
Active Motion Control
CT-RCEM
Ω𝑖𝑖+1 = Ω𝑖𝑖 + 𝑘𝑘 × 𝑒𝑒𝑖𝑖;𝑒𝑒𝑖𝑖 = Λ𝑑𝑑𝑒𝑒𝑑𝑑 − Λ𝑖𝑖
Control Law
Abhinav Tripathi, Prof Zongxuan Sun
Experimental Validation –Simplified Problem
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• Reduced computational burden for supervisory control
• True sinusoid represented by Ω = 1
• Piston spends more time at high P-T conditions (near TDC)
for trajectories with higher omega
• Effective means for controlling combustion phasing by
modulating the duration of time spent by fuel-air mixture at
high pressure and temperature conditions near TDC
Parameterize piston trajectory in terms of shape parameter 𝜴𝜴
0 5 10 15 20 25 30 35 40
Time (ms)
0
25
50
75
100
125
Posi
tion
(mm
)
Piston trajectories characterizedby shape parameter
=0.6
=1.0
=1.4
0 5 10 15 20 25 30 35 40
Time (ms)
-15
-10
-5
0
5
10
15
Velo
city
(m/s
)
-180 -120 -60 0 60 120 180
Crank Angle (deg)
Abhinav Tripathi, Prof Zongxuan Sun
Controlled Trajectory Rapid Compression and Expansion Machine
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CT-RCEM uses an electro-hydraulic actuator with feedback control to drive the piston
- Developed at University of Minnesota
under 3 year NSF-MRI Grant
- High throughput and extreme operational
flexibility
- Ability to control the piston trajectory inside
the combustion chamber
Same CRDifferent compression times
Different CRSame compression time
reference trajectory
Abhinav Tripathi, Prof Zongxuan Sun
Setup and Specifications Maximum Combustion Pressure 250 bar
Minimum Compression Time 20 ms
Maximum Compression Ratio 25
Combustion Chamber Bore 50.8 mm
Maximum piston travel 192 mm
TDC clearance 8 mm
Hydraulic Working Pressure 350 bar
Hydraulic Piston Bore 40 mm
Mass of Piston Assembly 1.7 kg
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Key requirement:High-force and high-speed
actuation
Abhinav Tripathi, Prof Zongxuan Sun
Operational Flexibility of CT-RCEM
Inert mixture testing
Ensemble average for four repetitions of compression of Air-CO2 mixture
• Compression ratio: 12.4, 14.2, 15.5, 16.7
• Compression time: 20 ms & 30 ms
Enables calibration of heat transfer models using experimental data over a wide range of operating conditions
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Uniquely suited for experimental validation of trajectory based
combustion control
Abhinav Tripathi, Prof Zongxuan Sun
Repeatability of CT-RCEM
Four repetitions for CR: 16.7, compression time 20 ms.
Maximum deviation of individual pressure profiles from ensemble average of repetitions ≈ 0.2 bar
Repeatability Analysis for Compression ratio 16.7
Stroke 131 mm
Compression time 20 ms
Peak velocity 12.5 m/s
Peak tracking error 0.6 mm
Average velocity 7 m/s
Peak flow rate 920 l/min
Peak instantaneous power 0.4 MW
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Abhinav Tripathi, Prof Zongxuan Sun
Mimicking Engine Operation in CT-RCEM
0 10 20 30 40 50 60
Time (ms)
0
20
40
60
80
100
120
140
Posi
tion
(mm
)
Piston Trajectory
rep1
rep2
0 10 20 30 40 50 60
Time (ms)
0
5
10
15
20
25
Pres
sure
(bar
)
Gas Pressure
rep1
rep2
0 10 20 30 40 50 60
Time (ms)
-1
-0.5
0
0.5
1
Erro
r (m
m)
Tracking Error
rep1
rep2
• Investigating partial ignition of DME for engine-like sinusoidal trajectory
• Fuel mixture – DME:O2:N2 = 1:4:40 (lean and diluted with extra nitrogen)
• Stroke: 121 mm, CR: 15.5, RPM: 1500• Creviced piston to trap boundary layer
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Abhinav Tripathi, Prof Zongxuan Sun
Experimental Results
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0 10 20 30 400
20
40
60
80
100
120
140
Pos
ition
(m
m)
0
20
40
60
80
Pre
ssur
e (b
ar)
Effect of piston trajectory on combustion for T 0= 45C
0 10 20 30 40
Time (ms)
-1.5
-1
-0.5
0
0.5
1
1.5
Erro
r (m
m)
Tracking error for different
1=1.2
2=1.0
3=0.8
• HCCI combustion of premixed dimethyl-ether (DME)• CR 12.1, equivalent operating speed 1500 rpm• Fuel-air equivalence ratio (𝜙𝜙) 0.6• Initial conditions: 𝑇𝑇0 = 45°𝐶𝐶;𝑃𝑃0 = 1.03 𝑏𝑏𝑏𝑏𝑏𝑏• Desired LPP Λ𝑑𝑑𝑑𝑑𝑑𝑑 = 5° crank angle after TDC
Supervisory control adjusts piston trajectory until 𝜦𝜦𝒅𝒅𝒅𝒅𝒅𝒅 is attained
Abhinav Tripathi, Prof Zongxuan Sun
Experimental Results
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Trajectory based combustion control is an
effective method for combustion phasing control
Iteration Ω𝑖𝑖 Λ𝑖𝑖 Req δΩ𝑖𝑖 Actual Ω𝑖𝑖+1
𝑖𝑖 = 1 1.2 0.4° 0.27 1.0
𝑖𝑖 = 2 1.0 3.1° 0.12 0.8
𝑖𝑖 = 3 0.8 5.4° - -
For implementation purpose, resolution of Ω has been limited to ±0.2 for this study
Heat release at TDC (Otto cycle)
Heat release at Λ ≈ Λ𝑑𝑑𝑑𝑑𝑑𝑑
Abhinav Tripathi, Prof Zongxuan Sun
Heat Release Analysis
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19 19.5 20 20.5 21
Time (ms)
0
200
400
600
Hea
t Rel
ease
(J)
Heat release analysis for T0
= 45 0 C
0.8
1
1.2
Qf
𝑑𝑑𝑄𝑄𝑏𝑏𝑎𝑎𝑎𝑎 =𝛾𝛾
𝛾𝛾 − 1𝑃𝑃𝑑𝑑𝑃𝑃 +1
𝛾𝛾 − 1𝑃𝑃𝑑𝑑𝑃𝑃 −𝑃𝑃𝑃𝑃
𝛾𝛾 − 1 2 𝑑𝑑𝛾𝛾
Initial temperature 45°𝐶𝐶
Omega 1.2 1.0 0.8
LPP (°𝐶𝐶𝐶𝐶) 0.37° 3.24° 5.41°
Comb. efficiency (𝑄𝑄𝑏𝑏𝑎𝑎𝑎𝑎/𝑄𝑄𝑓𝑓) 90.9% 89.4% 90.6%
Indicated thermal efficiency 19.5% 21.4% 23.6%
• Piston spends less time near TDC for trajectories with lower omega leading to:
• lower heat loss
• less time for completion of combustion reactions
• Indicated thermal efficiency trend is dominated by heat loss effects for this operating point
• Significant dependence of indicated thermal efficiency on piston trajectory
• Excessive heat loss in the CT-RCEM due to large stroke to bore ratio
𝑑𝑑𝑄𝑄𝑏𝑏𝑎𝑎𝑎𝑎 = 𝑑𝑑𝑄𝑄𝑐𝑐𝑐𝑐𝑐𝑐𝑏𝑏 − 𝑑𝑑𝑄𝑄𝑙𝑙𝑐𝑐𝑑𝑑𝑑𝑑 = 𝑑𝑑𝑑𝑑 + 𝑃𝑃𝑑𝑑𝑃𝑃
𝑄𝑄𝑏𝑏𝑎𝑎𝑎𝑎 = �𝑡𝑡𝑑𝑑𝑐𝑐𝑐𝑐
𝑡𝑡𝑒𝑒𝑐𝑐𝑐𝑐𝑑𝑑𝑄𝑄𝑏𝑏𝑎𝑎𝑎𝑎 𝑄𝑄𝑓𝑓 = 𝑐𝑐𝑓𝑓𝐿𝐿𝐿𝐿𝑃𝑃𝑓𝑓
Abhinav Tripathi, Prof Zongxuan Sun
Conclusions
• Framework for implementation of trajectory based combustion control strategy for Free Piston Engine operation has been presented
• A controlled trajectory rapid compression and expansion machine has been developed at UMN for addressing the research needs of fundamental and applied combustion investigation
• Hardware-in-loop framework has been proposed for experimental validation of trajectory based combustion control
• Experimental results show that piston trajectory is an effective method for combustion phasing control
• Ongoing work includes extending the hardware-in-loop framework for efficiency analysis of a modular electrical free piston engine operating on trajectory based combustion control
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