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Bridging the Gap Between Fundamental Physics And BridgingBridging thethe GapGap betweenbetween FundamentalFundamental PhysicsPhysics andand ChemistryChemistry andand AppliedApplied ModelsModels forfor HCCIHCCI EnginesEngines Dennis N. Assanis DEER Conference August 20-25, 2005 Chicago, IL HCCI Engine Grand Challenges Physics Experiments Chemical Models Kinetics HCCI Combustion Sensors, Enabling Actuators, Technologies Control Bridging the Gap Between HCCI Fundamentals and Applied Models A University Consortium on Homogeneous Charge Compression Ignition Engine Research - Gasoline University of Michigan Dennis Assanis (PI), Arvind Atreya, Zoran Filipi, Hong Im, George Lavoie, Volker Sick, Margaret Wooldridge Massachusetts Institute of Technology Wai Cheng, William Green Jr., John Heywood Stanford University Tom Bowman, David Davidson, David Golden, Ronald Hanson, Chris Edwards University of California, Berkeley Jyh-Yuan Chen, Robert Dibble, Karl Hedrick HCCI University Consortium Acknowledgements Bridging the Gap Between HCCI Fundamentals and Applied Models Objectives Bridge the gap between fundamental HCCI physics and chemistry considerations and applied models ─ Balance model fidelity with computational expediency and ultimate goal in mind Demonstrate a cascade sequence where high fidelity models and experiments feed phenomenogical models appropriate for systems analysis Apply system models to assess candidate control schemes Multi-Variable RPM Engine Controller Requested Torque IN OUT SIGNALS IN: 1. Coolant temperature sensor 2. "Combustion" sensor : SIGNALS OUT: pressure transducer; or 1. Camless intake valve(s) timing novel SOC probe; or 2. Spark plug for DGI mode ionization probe 3. Fuel injector timing 3. Air mass flow sensor 4. Camless exhaust valve(s) timing 4. Intake manifold temperature sensor 5. EGR control valve 5. Intake manifold pressure sensor 6. Controllable water pump 6. Exhaust manifold temperature sensor 7. Exhaust manifold pressure sensor 8. Wide range oxygen sensor Bridging the Gap Between HCCI Fundamentals and Applied Models Approach Bridging the Gap Between HCCI Fundamentals and Applied Models Engine University Consortium Set-Ups UM Optical Engines UM Heat Transfer Engine Stanford Camless MIT VW Engine with VVT UCB VW TDI engine UCB CAT Single Cylinder Bridging the Gap Between HCCI Fundamentals and Applied Models Local Heat Fluxes 2.5 ] p2 2 2.0 HEAD TELEMETRY 1.5 1.0 0.5 spark H2 H1 Heat Flux [MW/m 0.0 -0.5 -120 -90 -60 -30 0 30 60 90 120 2.0 deg crank angle p3 ] 2 1.5 1.0 injector 0.5 PISTON 0.0 P7 [MW/m Flux Heat -0.5 -120 -90 -60 -30 0 30 60 90 120 P6 2.0 P2 crank angleh1 (deg) ] P1 2 1.5 P3 1.0 P4 0.5 0.0 P5 [MW/m Flux Heat -0.5 -120 -90 -60 -30 0 30 60 90 120 crank angle (deg) Bridging the Gap Between HCCI Fundamentals and Applied Models Concept of Modified Woschni Correlation Models need to be calibrated to provide Classic Woschni underpredicts heat accurate total heat loss transfer during compression and 2.5 leads to unrealistic ignition Spatially Averaged predictions Woschni ] 2.0 2 Reduced Woschni Modified Woschni heat transfer 1.5 model: ─Original: A = 1 1.0 2 ─Modified: A2 = 1/6 0.5 −−0.2 0.8 0.53 0.8 Heat Flux [MW/m 0.0 hB= χ Woschni 3.26 ⋅⋅⋅pT ⋅w VT -0.5 wCSC=+AAdr () P −P -90 -60 -30 0 30 60 90 1212p m prrV crank angle π Bwp CC12=+2.28 0.308 ,= 0.00324 S p Bridging the Gap Between HCCI Fundamentals and Applied Models Experimental Burn Rate Data 40 35 Varying RPM, load, T , T , A/F ratio 30 cool inlet 115C 25 Intake 105C 20 Temperature Generate correlations as function Increase 95C 15 85C of ignition timing (one variable) 10 75C w+1 5 x Δ−−−= θθθ ])/)((exp[1 Net Heat Release Rate [J/deg] NORM 0 0 -20 -10 0 10 20 30 40 Crank Angle (deg) BURN DATA COMBUSTION EFFICIENCY 40 100 CA90 CURVE FITS CURVE FIT DATA POINTS 30 EXPERIMENTAL DATA POINTS 95 20 CA50 10 CEF (%) CA10 CA (Deg ATC) 90 0 CA0 -10 85 -8 -6 -4 -2 0 2 -8 -6 -4 -2 0 2 CA0 (Deg ATC) CA0 (deg ATC) Bridging the Gap Between HCCI Fundamentals and Applied Models Modeling Approaches for HCCI Engines Detailed Multi-D Chemistry Quasi-D Reduced Detailed Zero-D Multi-zone Chemistry Chemistry Predictions of ignition Predictions of rate of burning ? Predictions of emissions ? Computational Efficiency Bridging the Gap Between HCCI Fundamentals and Applied Models Initial Modeling Approach: Sequential CFD + Multi-zone Model Open-cycle calculation 1 using Kiva-3V Calculation of combustion event using 3a Multi-zone model with Temperature Zones only TRANSITION POINT 2 Temperature / Equivalence Ratio Calculation of combustion event using distribution obtained before TDC 3b Multi-zone model with T/Φ Zones Bridging the Gap Between HCCI Fundamentals and Applied Models Sensitivity to Transition Timing Calculations at LLNL showed that the point of transition from KIVA to the multi-zone code can affect the results (SAE 2005-01-0115) ─ Imposed Φ distribution on a 2D coarse grid (Fuel CH4) ─ Solution obtained using sequential multi-zone approach compared against detailed solution (KIVA-3V linked with Chemkin) ─ Implication: Temperature and composition stratification is important 120 Full chemistry Centerline 110 in each cell Transition @ 20 BTDC 100 90 80 Transition @ 10 BTDC 70 Pressure [bar] Pressure 60 Transition @ 15 BTDC 50 40 -20 -10 0 10 20 Crank Angle Degree Bridging the Gap Between HCCI Fundamentals and Applied Models Naturally Occurring Thermal Stratification Collaboration with Sjöberg and Dec (Sandia) - SAE 2004-01-2994 Temperature field at TDC Centerline Temperature [K] 700 800 900 1000 Below 750 850 950 Above 0.15 330o Temperature and composition 340o distributions continue to evolve 0.1 until late in the compression 350o stroke. Decoupling of flow and 0.05 360o o chemistry is problematic. 380o 370 Mass Distribution Density 0 700 750 800 850 900 950 1000 1050 Temperature [K] Bridging the Gap Between HCCI Fundamentals and Applied Models Coupling of KIVA-3V with Multi-Zone Model (KMZ) Temperature and ϕ distributions Head Temp 2 High Low Piston Head ϕ High 3 1 Shaded part: Low rd Piston 3 Temperature zone (15-35%) Instead of solving for detailed chemistry in each cell, at each timestep divide into zones of cells with similar properties (i.e. Temperature zone T and ϕ), and assume they divided into ϕ zones behave in a similar manner Estimate composition change and heat released in each zone, and re-distribute 4 to corresponding KIVA-3V cells Bridging the Gap Between HCCI Fundamentals and Applied Models Validation of Fully Coupled Kiva-3V with Multi-Zone Model Mean Maximum Pressure Temperature Temperature 90 1800 2200 Full chemistry 1700 Full chemistry 85 in each cell in each cell 2000 ~100 zones 1600 ~100 zones 80 1800 1500 75 1400 1600 1300 Pressure [bar] Pressure 70 1400 Mean Temperature [K] Temperature Mean 1200 Full chemistry Maximum Temperature [K] 65 1200 in each cell 1100 ~100 zones 60 1000 1000 -5 0 5 10 15 20 25 -5 0 5 10 15 20 25 -5 0 5 10 15 20 25 Crank Angle [degree] Crank Angle [degree] Crank Angle [degree] The new model gives results that match very well the “exact” solution obtained by solving for detailed chemistry in every cell Computational time is reduced significantly (~90% for 10,000 cells) Bridging the Gap Between HCCI Fundamentals and Applied Models Numerical Experiments: KMZ generated “data” Run T sweeps of KMZ model for various operating parameters Generate burn angles as function of ignition timing, as well as other variables ALL BURN RESULTS (KIVA-CHEMKIN) Variable Sweeps 40 CR 16, 9 1% of fuel 30 10% burned RPM 2000, 1200 50% burned 90% burned Load (fuel) 9, 13 mg 20 BURN DATA CA90 40 CA90 CURVE FITS 30 10 CA50 EXPERIMENTAL DATA POINTS 20 CA10 Experimental CA50 Burn Angles (deg ATC) 0 Data 10 CA0 CA10 CA (Deg ATC) 0 CA0 -10 -8 -6 -4 -2 0 2 -10 -8 -6 -4 -2 0 2 CAD (deg ATC) CA0 (Deg ATC) Bridging the Gap Between HCCI Fundamentals and Applied Models System Studies Approach Use GT-Power as platform for system modeling Use experiments and CFD models to provide simplified combustion models with correct trends for ignition, burn rates and combustion efficiency Develop single-cylinder engine model with manifolds including thermal system submodel Explore implementation issues at multi-cylinder and vehicle level, especially related to thermal transients GT-POWER INTAKE COMPRESSION COMBUSTION EXHAUST Heat Heat Heat Heat transfer transfer release transfer coefficient coefficient rate coefficient BURN DATA 40 CA90 DLL CURVE FITS 30 EXPERIMENTAL DATA POINTS -ENGHEATTRUSER 20 IGN DELAY COMB. CORR. CA50 - ENGCOMBUSR 10 CA10 CA ATC) (Deg 0 CA0 4− 1 . − 05 − 0 . 771− . 41 (τ )ms= 1 . × 3 10 ⋅P φ ⋅ χexp( ⋅ ⋅ 33700RT / ) -10 ign O2 cal[//] mol K -8 -6 -4 -2 0 2 CA0 (Deg ATC) Bridging the Gap Between HCCI Fundamentals and Applied Models Thermal Transients – Simulating the UM Engine 12 EXH INT 10 ) 8 m m ( 6 T F SI mode LI 4 4 2 0 -270 -180 -90 0 90 180 270 3 480 CA (deg ATC) AVERAGE 4 WALL TEMPERATURE 1 2 460 HCCI mode,SAE 2002-01-0420 440 T (K) 3 420 2 400 1 380 0204060 time (sec) Bridging the Gap Between HCCI Fundamentals and Applied Models Thermal Transients – Challenges Stable operation possible at steady state thermal points 60 P3T4 50 Advanced / knocking 40 P 30 P3T3 480 (bar) AVERAGE 20 4 WALL TEMPERATURE 460 10 Point 3 at Steady State T3 Point 3 at T4 (hot - knocking) Retarded / misfire 440 0 T (K) -20-100 10203040 40 3 420 CA (deg ATC) P2T1 2 30 400 1 P2T2 P 380 20 0204060 (bar) time (sec) 10 Point 2 at Steady State T2 Point 2 at T1 (cold - misfire) Transient operation unsatisfactory 0 -20-100 10203040 CA (deg ATC) Bridging the Gap Between HCCI Fundamentals
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