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Integrated Aftertreatment System Modeling Using GT-POWER
Syed Wahiduzzaman, Weiyong Tang and Seth Wenzel Gamma Technologies 10th DOE Crosscut Workshop on Lean Emissions Reduction Simulation May 1st - 3rd, 2007
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Motivations Motivations
Tremendous need for the ability to simulate AT systems Design/development process is increasingly a collaborative endeavor Variety of domain experts (e.g. test, performance, AT systems, control/calibration) frequently using disparate tools Overall system optimization is ultimately the goal A common simulation environment is a necessity
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Goals and Approach Goals Approach Provide an integrated tool
Flexible environment capable of handling customized kinetics Facilitate communication and collaboration between various domain experts Minimize learning curve Eliminate the need of users written code to input kinetics Approach Specialized AT object (DPF, CatalystBrick) as flow component Chemistry library templates to input customized kinetics Built directly into GT-Power library sharing existing capabilities, look and feel
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Concept: Chemistry Library Templates
Burner, hydrolysis Catalyst ChemKin Catalyst with storage “GaseousReactions”: Standard gas phase reactions “Global-Reactions”: Global reactions with stoichiometric and non-stoichiometric concentrations and Langmuir-Hinshelwood expression “SurfaceReactions”: Same as GlobalReactions but additionally supports surface reactions with coverage (storage) calculations
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Geometric and Thermal Specifications
Catalyst Brick Diesel Particulate Filter 1D > 0D : it can be 10 to 50 times faster. 0D or 1D
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Kinetics Specification
GlobalReactions Template
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Principle Chemistry component turns a flow component into a reactor when connected to it Two of the main design objectives of the kinetics modeling environment are that it must be flexible such that it can be adapted to versatile chemical mechanisms and accessible to simulation engineers who are not necessarily experts in chemical kinetics. In this regard a set of objects (Chemistry Library Objects) are designed that are able to accept inputs for gaseous, global and surface reaction kinetics in an intuitive manner. Lean Nox Trap: dedicated for light-duty diesel At lean conditions, it reduct NO in N2 without additional ammonia like in SCR. The material are expensive.
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Collaborative Simulations
Test cell data: Calibration of engine models, generation maps and fits (e.g. emissions, mean value, neural network models) Generation of boundary conditions for standalone simulation of AT unit models (e.g. simulated test cycle data) Validation of unit models Integration of unit models into system model Control system modeling
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Generation of BC for Standalone AT Models
EngCylEmisMaps (from Test cell) SpeciesSampler
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To AT Group SpeciesSampler Output: Pressure Concentrations Temperature
Flow Rate
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An standalone Model for Catalyst Domain Experts
SpeciesSampler or Experimental Data CatalystBrick Kinetics
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Examples and Applications
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DPF Model Lumped model 1D quasi-steady model
Uniform temperature at gas and solid phases Uniform wall flow distributions Computational efficiency 1D quasi-steady model Axially different temperature and pressure Non-uniform wall flow distributions Detailed information
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Deep Bed Filtration/Pressure Drop
Deep-Bed Filtration Model Study deep bed filtration using theories of uniform spherical collectors and Brownian diffusion.
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Experimental Validations
Table 1: DPF Specifications for Simulation Type EX-80* CCRT** Trap Diameter (mm) 229 267 Channel Length (mm) 305 Channel Width (mm) 1.5 1.49 Wall Thickness 0.31 0.305 Number of Inlet Channels 6013 8659 Wall Porosity 0.48 0.52 Pore Diameter (mm) 0.0125 0.013 Bulk Density (kg/m3) 1400 Specific Heat (J/kg-K) 1120 Thermal Conductivity (W/m-K) 2.092 * Uncatalyzed, made by Corning; ** Catalyzed, made by Johnson Matthey.
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Experimental Validation: with an Uncoated EX-80
Symbols: measurements as Fig. 5 in SAE ; Lines: predictions.
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Experimental Validations: with an Coated CCRT
Symbols: measurements as Figs. 5&6 in SAE ; Lines: predictions.
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Experimental Validation: Active Regeneration by Fuel Injection
Symbols: measurements as Figs. 8&A.2 in SAE ; Lines: predictions.
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Kinetics Templates
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GaseousReactions Template
Elementary gas-phase kinetic mechanisms Reactions can be directly typed into the template or imported from a file Advanced feature set Reversible and irreversible reactions Generalized Arrhenius formulation (A*f(T)*g(P)*Exp(-Ta/T)) Pressure-Dependent reactions, including: Third-body reactions Reactions with low pressure limit Troe falloff SRI falloff
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GlobalReactions Template
Global kinetic mechanisms Arbitrary reaction order and concentration expression Generalized inhibition functions including Langmuir and Hinshelwood type Support various types of rate specifications Diffusion from and to surface
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SurfaceReactions Template
All relevant features of GlobalReactions Template Coverage calculation Supports storage and arbitrary functions of coverage in the rate specification
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Building a SCR Model Step 2: Link parts to create a flow model
Step 1: Place necessary flow objects into project map Note reaction kinetics has not yet been specified to the SCR.
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Building a SCR Model (Cont.)
Step 3: Input global kinetics to a chemistry template and link it to flow object SCR-01 Global kinetics
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Building a SCR Model (Cont.)
Step 4: Construct associated control and sensor parts Reaction kinetics Catalytic device NH3 injection controller Species sensors and NOx conversion cal.
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Building a SCR Model (Cont.)
Step 5: Unit model testing, calibration and validation
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Building a SCR Model (Cont.)
Step 6: Add subsytems
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Building a SCR Model - Advanced
User can optionally account for NH3 storage using ‘SurfaceReactions’ template: Absorption: NH3 + S -> S(NH3) Desorption: S(NH3) -> NH3 + S Where ‘S’ represents a general surface site. Specific sites can also be studied: WO3, Ti2O, V205
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Building a SCR Model - Advanced
User can optionally account for NH3 storage using ‘SurfaceReactions’ template:
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Building a SCR Model - Advanced
Desorption: S(NH3) -> NH3 + S Steady State Absorption: NH3 + S -> S(NH3)
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Building a SCR Model - Advanced
User can optionally account for NH3 storage using ‘SurfaceReactions’ template:
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DOC + LNT Example Lean Nox Trap (LNT) Reactions:
NOx storage forming nitrite: BaCO3 + 2NO2 + .5O2 => Ba(NO3)2 + CO2 BaCO3 + 2NO + 1.5O2 => Ba(NO3)2 + CO2 NOx regeneration: NOx release: Ba(NO3)2 + 3CO => BaCO3 +2NO + 2CO2 Ba(NO3)2 + H2 + CO2 => BaCO3 +2NO2 + H2O NOx reduction: CO + NO => 0.5N2 + 2CO2 NO2 <=> NO + 0.5O2
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Diesel Oxidation Catalyst (DOC) Reactions:
DOC + LNT Example Diesel Oxidation Catalyst (DOC) Reactions: CO + 0.5O2 => CO2 C3H O2 => 3CO2 + 3H2O H O2 => H2O NO+0.5O2 => NO2 NO2 => NO+0.5O2 HC O2 => 14.6CO H2O Note HC stands for diesel fuel (C14.6H24.8).
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DOC + LNT Example
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DOC + LNT Example
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Lean Operation 0-10s Rich Operation 10-20s
DOC + LNT Example Lean Operation 0-10s Rich Operation 10-20s
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Kinetic Parameter Identification
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GlobalReactions Template
Application: Three-Way Catalyst CO oxidation: CO + 0.5O2 => CO2 HC (unburned and partially burned) oxidations: CH4 + 2O2 => CO2 + 2H2O C3H O2 => 3CO2 + 3H2O C3H8 + 5O2 => 3CO2 + 4H2O NO oxidation: CO + NO => CO N2 NO + 0.5O2 => NO2 NO2 => NO + 0.5O2 H2O formation: H O2 => H2O
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Kinetics of 3-Way Catalyst
Global Reaction Scheme Individual Production Rates: Inhibition Terms: K expressions for near equilibrium behavior:
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Parameter Identification
Original kinetic set is not applicable and has to be calibrated Parameter optimization are often carried out on: Pre-exponential factor Ai Activation temperature/energy Ei Optimization of a total of 16 parameters 8 reactions x 2 values = 16 parameters Design of Experiments (DoE)
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TWC: Experimental Inlet Conditions
Minor species inlet mole fractions Inlet exhaust temperature and mass flow rate
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Test Rig Model Global Reactions used to define chemical kinetics
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Error = Sum{(measured-predicted)^2}
Test Rig Model (Cont.) Error = Sum{(measured-predicted)^2} User Defined Error Function Input for Measured Data
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DOE Sensitivity Study Built-in DOE tools is used to perform sensitivity study Latin Hypercube partial factorial
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DOE Sensitivity Results
Sensitivities Error Function value of 200 experiments
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DOE Sensitivity Study Discovered that the following 3 equations most significantly affected results: R1 and R4 most sensitive R2 also sensitive R1 R4 R2
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Final Optimized Parameters
Pre-exponential factor, Ai (mole•K/cm3•S) Activation temperature, Ei (K) Original 1 1.0E+11 9622 2 1.39E+13 12500 3 3.66E+6 16000 4 2.2E+7 10171 5 6.7E+7 2000 6 7 4.5E+9 8 1.0E+9 Optimum 1.04E+11 1.39E+12 11000 3.66E5 16000 3.37E+7 8.00E+6 2100 1.43E+09 7.71E+7
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System Integration and Simulation
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Integrated Model of Engine, Vehicle and DPF Systems
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Typical Results of System Simulation
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Summary I Highly comprehensive and flexible solution: not hardwired
Specialized models for DPF General tools for chemical/catalytic reactions Solves user supplied reaction sets (mechanisms) Can be encrypted into a subassembly or compound object (black-box) Integrated tool: multiple catalysts in series (+engine + vehicle)
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Summary II Single simulation environment (no third party tool is needed) Built-in DOE optimization for parameter identification Can be run as standalone unit model or as integrated simulation in GT-SUITE
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New Developments Faster Solvers 2-D Conduction in
Method of lines (Cavendish, Oh, Bissett) Quasi-steady hybrid-boundary solution Up to two orders of magnitude faster 2-D Conduction in CatalystBrick and DPF Kinetics-based combustion and emissions models
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Thank You! 10th DOE Crosscut Workshop on Lean Emissions Reduction Simulation May 1st - 3rd, 2007
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