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Abhinav Tripathi, Prof Zongxuan Sun
Abhinav Tripathi
Professor Zongxuan Sun
Department of Mechanical Engineering
University of Minnesota
Modeling and Optimization of Trajectory-based
Combustion Control
1
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
– A novel instrument Controlled Trajectory Rapid Compression and Expansion Machine (CT-RCEM)
– Unique capabilities of CT-RCEM
– Experimental characterization of CT-RCEM
• Conclusions
2
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
Em
issio
n p
erf
orm
ance Spark Ignition
Engine
Diesel
Engine
LTC
Engine
3
Global trend - tighter regulations for fuel efficiency and emissions
Abhinav Tripathi, Prof Zongxuan Sun
Background – HCCI Combustion
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
Challenge - Combustion phasing
Control of ignition timing to achieve continuous operation is extremely
difficult in conventional ICE
4
Abhinav Tripathi, Prof Zongxuan Sun
Opposed Piston Opposed Cylinder Engine
No mechanical crankshaft
Direct Fuel Injection
Background – FPE at UMN
Variable compression ratio
•Advanced combustion strategy
•Multi-fuel operation
Reduced frictional losses
Faster response time
5
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
Abhinav Tripathi, Prof Zongxuan Sun
Background – FPE at UMN
6
Abhinav Tripathi, Prof Zongxuan Sun
Presentation Outline
• Motivation, Background and Objective
• Trajectory-based HCCI Combustion Control
– Previous Work: Modeling and Optimization Framework
• Approach for experimental validation
– A novel instrument Controlled Trajectory Rapid Compression and Expansion Machine (CT-RCEM)
– Unique capabilities of CT-RCEM
– Experimental characterization of CT-RCEM
• Conclusions
7
Abhinav Tripathi, Prof Zongxuan Sun
Chemical Kinetics of Fuel
In-cylinder Gas Dynamics
Thermal heat releaseReaction productReaction rate
PressureTemperatureSpecies 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
8
Free Piston
Engine
Abhinav Tripathi, Prof Zongxuan Sun
Optimal Trajectories
Control Signals
Piston displacement
In-cylinder gas volume, pressure, temperature and major chemical spices concentration
Model Based Trajectory
Optimization
Active Motion Control (Virtual
Crankshaft)
Inner Loop: piston motion control - virtual crankshaft
Outer Loop: Trajectory-based combustion control
Basic Framework - Trajectory-based Combustion Control
9
Abhinav Tripathi, Prof Zongxuan Sun
Presentation Outline
• Motivation, Background and Objective
• Trajectory-based HCCI Combustion Control
– Previous Work: Modeling and Optimization Framework
• Approach for experimental validation
– A novel instrument Controlled Trajectory Rapid Compression and Expansion Machine (CT-RCEM)
– Unique capabilities of CT-RCEM
– Experimental characterization of CT-RCEM
• Conclusions
10
Abhinav Tripathi, Prof Zongxuan Sun
Controlled Trajectory Rapid Compression and Expansion Machine
- 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
CT-RCEM is new instrument that uses fluid power to enable unique experimental
capabilities for fundamental and applied combustion research
11
Abhinav Tripathi, Prof Zongxuan Sun
CT-RCEM – What’s unique?
CT-RCEM uses an
electro-hydraulic actuator
with feedback control to
drive the piston
Reference trajectory is fed
electronically to the controller
Same CR
Different
compression times
Different CR
Same compression
time
reference
trajectory
12
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
13
Key requirement:
High-force and high-speed
actuation
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
14
Abhinav Tripathi, Prof Zongxuan Sun
Mimicking Engine Operation
in CT-RCEM
• 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
15
Abhinav Tripathi, Prof Zongxuan Sun
HCCI Combustion for an FPE
Trajectory
10 15 20 25 30 35 40 45 50
Time (ms)
0
20
40
60
80
100
120
Po
sitio
n (
mm
)
Piston Trajectory
-180 -120 -60 0 60 120 180
Crank Angle
• Autoignition test for DME
• Fuel-air equivalence ratio (ɸ) 0.75
• Initial temperature 50°C• Initial pressure 15 psi
• Ambient pressure 14.15 psi
• Stroke: 121 mm, flat piston
• CR: 11.3, 1500 rpm
10 15 20 25 30 35 40 45 50
Time (ms)
0
200
400
600
800
1000
1200
Pre
ssu
re (
psi)
Gas Pressure
-180 -120 -60 0 60 120 180
Crank Angle
25 26 27 28 29 30 31 32 33 34 35
Time (ms)
0
200
400
600
800
1000
1200
Pre
ssu
re (
psi
)
Gas Pressure
-45 -30 -15 0 15 30 45
Crank Angle
16
Abhinav Tripathi, Prof Zongxuan Sun
10 15 20 25 30 35 40 45 50
Time (ms)
0
20
40
60
80
100
120
Po
sitio
n (
mm
)
Piston Trajectory
Same speed same CR different shape
w: 1.2
w: 1.0
w: 0.8
-180 -120 -60 0 60 120 180
Crank Angle
10 15 20 25 30 35 40 45 50
Time (ms)
0
20
40
60
80
100
120
Po
sitio
n (
mm
)Piston Trajectory
Same speed different CR
CR: 9.5
CR: 10.4
-180 -120 -60 0 60 120 180
Crank Angle
0 10 20 30 40 50 60
Time (ms)
0
20
40
60
80
100
120
Po
sitio
n (
mm
)
Piston Trajectory
Same CR different speed
1500 rpm
1000 rpm
-180 -120 -60 0 60 120 180
Crank Angle
Producing different FPE
Trajectories
10 15 20 25 30 35 40 45 50
Time (ms)
0
20
40
60
80
100
120
Posi
tion
(m
m)
Piston Trajectory
Asymmetric operation
w: 1.2
wc:1.2 - we: 0.8
-180 -120 -60 0 60 120 180
Crank Angle
Unique ability to electronically change CR, speed and shape of piston
trajectory allows reproduction of any FPE trajectory
Further development is
underway to demonstrate the
intake and exhaust stroke, and
spark ignition
17
Abhinav Tripathi, Prof Zongxuan Sun
CT-RCEM for Engine Applications – FPE and Conventional ICE
• Scope to incorporate multi-cycle testing
• Flexibility to accurately pre-set initial conditions (charge pressure and temperature)
• Flexibility to accommodate in-situ or ex-situ species diagnostics through optical
(chemiluminescence, LIF) or gas sampling methods (GCMS)
• Replaceable head design to incorporate direct injection, spark plug, or intake
manifold as required
• Uniquely suited for investigating turbocharged combustion modes
• Replaceable piston crown to enable evaluation of piston crown geometries
• Flow field and turbulence studies by using various piston designs, changing piston
trajectories or even including an intake stroke
18
Abhinav Tripathi, Prof Zongxuan Sun
Optical Diagnostics – Accessing Chemical Kinetics Information
30 ms compression 20 ms compression
30 ms 20 ms
• Optical measurement work
by capturing the
fluorescence of
intermediate species
• Chemiluminescence or
Laser induced fluorescence
• Measurement of
intermediate species such
as OH*, CH*, CH2*
• Comparing image
intensities gives a
quantitative estimate of
species concentration
Camera
Combustion
chamber
Piston
19
Abhinav Tripathi, Prof Zongxuan Sun
Conclusions
• A controlled trajectory rapid compression and expansion machine has been developed at
UMN for addressing the research needs of fundamental and applied combustion
investigation
• The exceptional flexibility and the novel capabilities have been demonstrated
• CT-RCEM offers a unique opportunity to experimentally validate the concept and
framework of trajectory based combustion control
• We are looking for opportunities to collaborate to further develop and demonstrate the
capabilities of the CT-RCEM.
20
Abhinav Tripathi, Prof Zongxuan Sun21
Backup Slides
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
22
Uniquely suited for experimental
validation of trajectory based
combustion control
Abhinav Tripathi, Prof Zongxuan Sun
Simulating FPE Operation
• Piston position and actual pressure
shown here is measured data
• Adiabatic pressure, isothermal
pressure, and temperature traces
are estimated
23