Demonstrating Optimum HCCI Combustion with … Optimum HCCI Combustion with Advanced Control . ... C...
Transcript of Demonstrating Optimum HCCI Combustion with … Optimum HCCI Combustion with Advanced Control . ... C...
Demonstrating Optimum HCCI Combustion with Advanced Control
Technology Nick Killingsworth Salvador Aceves Dan Flowers Francisco Espinosa-Loza Tim Ross Lawrence Livermore National Laboratory Livermore, California
Miroslav Krstic Department of Mechanical and Aerospace Engineering University of California, San Diego
HCCI combustion occurs when premixed mixture autoignites, no direct trigger to initiate combustion
Premixed fuel and air Mixture compressedinducted into cylinder until it autoignites Mixture expands
In-C
ylin
der
Pre
ssur
e
Crank Angle
There is a window of allowable HCCI engine combustion timings due to constraints
Peak Pressure/ Peak Pressure Rise Rate
NOx Limit
Misfire Limit/ CO & UHC Limit
Load
Combustion Timing
A Proportional-Integral-Derivative (PID) controller has three terms
error e(t)+
-
+ Controlled System
measured output
Up
Ui
Ud
+
+
desired output U
- Proportional to error: uP (t) = tKe( )
- Integral of error : uI (t) = IT
K ∫0
te(s)ds
de(t)- Derivative of error: uD (t) = KTD dt
PID controller takes control action based on past, present, and future control errors
t t+Td
Erro
r
Time
Present
FuturePast
error+
-
+ Controlled System
measured output
Up
Ui
Ud
+
+
desired output
Gain scheduling of PID parameters required due to
nonlinear nature of HCCI engines Gain Scheduled PID Parameters (K,TI ,TD)
IMEP RPM
0-1 [bar]
1-2 [bar]
2-3 [bar]
3-4 [bar]
0-1000 PID1,1 PID1,2 PID1,3 PID1,4
1001-2000 PID2,1 PID2,2 PID2,3 PID2,4
2001-3000 PID3,1 PID3,2 PID3,3 PID3,4
3001-4000 PID4,1 PID4,2 PID4,3 PID4,4
4001-5000 PID5,1 PID5,2 PID5,3 PID5,4
Online non-model based
controller tuning methods are desirable
• Many methods have been developed – Model based methods
• Model must be derived or estimated • Controller parameters calculated offline
– Non-model based methods • Require offline calculations
– Extremum Seeking • Non-model based • Online tuning procedure
We have applied extremum seeking to tune HCCI combustion timing controller
Experimental HCCI engine setup
)( ky
hz z
+ − 1×+
( )θJ
)cos( kωα )cos( kωα
)(kθ
1−− z
γ
Extremum seeking controller tuning scheme
0 100 200 300 400 500 600 700 50
60
70
80
C o l
d V a
lve
P o si
tio n
(% c
lo s e
d
0 100 200 300 400 500 600 700
6
8
10
12
cycle number
CA
5 0 (C
AD
a T D
C )
setpoint Cylinder 1
Experimental controller tuning
Caterpillar 3406 operated at LLNL the platform for control experiments
• Converted 3406 spark ignited engine
• 15L 6-cylinder engine
Intake temperature effective means to control combustion timing
Heated Intake Mixture
Cooled Intake Mixture
Mixing “Tees”(x 6)
Each cylinder’s intake temperature controlled individually
“Cold” Manifold
“Hot” Manifold
Mixing Tees
Intake 1: Cold
Intake 2: Hot
Carb
Generator
Thr
SC
Exhaust Manifold
T
Intake 1: Cold
Intake 2: Hot
Carb
Generator
Preheater
Intercooler
Thr
SC
Exhaust Manifold
T
Schematic of the HCCI engine and thermal management system used in experiments
Air
Fuel
Load
Carb = CarburetorT = TurbineC = CompressorThr = ThrottleSC = Supercharger
C
ExhaustTo preheater
Exhaust to Stack
Intake 1: Cold
Intake 2: Hot
Air
Fuel Carb
Air
Fuel
LoadGenerator Load
Carb = Carburetor T = Turbine C = Compressor Thr = Throttle SC = Supercharger
Preheater
Intercooler
CC Thr
Exhaust Manifold
TExhaustTo preheater
Exhaust to Stack
Exhaust To preheater
Exhaust to Stack
SC
Real-time control system utilizes cylinder pressure measurements as feedback signal
Real-Time Controller PC running Labview RT OS
Cylinder Pressure
Crank Angle Position
Valve Position
User interface
PIDController
Extremum seeking minimizes cost function by tuning the controller parameters
Square Wave CA50 Reference Signal Intake
HCCI Engine
Calc. CostCA50TemperaturePID Function
Extremum Seeking
Algorithm
Controller Parameters
Controller
Cost
Label things animate
Cost function calculated as combustion timing responds to square wave setpoint change
0 100 200 300 400 500 6005
6
7
8
9
10
11
12
CA
50 (d
eg a
tdc)
setpoint measured
Cost Cost New PID Parameters
New PID Parameters
cycle number
Combustion timing varied from 6 to 10 CAD ATDC, cost function only calculated at later timing (10 CAD ATDC)
Extremum seeking: non-model-based optimization method
+
θ (k)
×
( ) y(k)J θ
Function we are trying to optimize
−γ z −1 z + hz −1
High Pass Filter removes DC component of output y(k)
α cos(ωk) αcos(ωk) Demodulate by multiplication with αcos(ωk), this picks out portion ofPerturb system in order output due to perturbation, αcos(ωk)to generate gradient
Estimate of gradient is then integrated to yield a new θ closer to θ*
0 500 1000 1500 2000 2500 30000
2
4
J(θ)
0 500 1000 1500 2000 2500 30000
1
2
3
time (sec)
PID
Par
met
ers K
10Ti
Extremum seeking used to tune a PI controller for improved setpoint response of combustion timing
14
CA
50 (d
eg a
tdc) 12
10
8
6
setpoint measured
0 500 1000 1500 2000 2500 3000
4
1414
1212
8
CA
50 (C
AD
ATD
C)
1010
CA
50 (C
AD
ATD
C)
6 6
4 4
500 505 510 515 520 525 530 535 540 545 550 3000 3005 3010 3015 3020 3025 3030 3035 3040 3045 3050
8
Cylinder 1
PI controller tuned for fast setpoint response
results in high controller gains
50
60
70
80
Col
d Va
lve
Posi
tion
(% c
lose
d
setpoint 0 100 200 300 400 500 600 700
CA
50 (C
AD
aTD
C) 12
10
8
6
cycle number 0 100 200 300 400 500 600 700
A feedforward term was added to the PI controller
error+
-
+ Controlled System
measured output
Uff
Up
Ui
+
+
desired output, r(t)
- Constant feedforward term: u (t) = K ff r(t) ff
CA
50 (C
AD
aTD
C)
Col
d Va
lve
Posi
tion
(% c
lose
d PI + feedforward controller tuned using ES
feedforward results in less high frequency gain
60
70
80
50 0 100 200 300 400 500 600 700
12
10
8
6
cycle number
setpoint Cylinder 1
0 100 200 300 400 500 600 700
ES optimized PI and PI+FF controllers able to hold
constant combustion timing during load disturbance
1500
1600
1700
RPM
PI PI+FF
0
5
10
CA
50 (C
AD
aTD
C) 20 40 60 80 100 120 140 160 180 200
Varia
nce
of C
A50
0 20 40 60 80 100 120 140 160 180 200
2
1
0 0 20 40 60 80 100 120 140 160 180 200
Time (seconds)
ES scheme used to minimize fuel consumption of experimental HCCI engine
by determining optimal combustion timing setpoint
HCCI Engine
e CA50
CA50SP
-Tintake
CA50 + Σ PI
Extremum Seeking
mfuel .
ES delays the combustion timing 6 CAD reducing fuel consumption by more than 10%
Extremum Seeking is a useful tool
for rapidly improving HCCI controller performance
• We use ES to tune various forms of PID controllers while the engine is operating
• ES can also be used to optimize performance parameters (such as minimize fuel consumption)
• ES greatly aids in automating and optimizing the development of controllers for nonlinear systems like HCCI engines