1. 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

2. 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

3. 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

4. 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

5. Geometric and Thermal Specifications
Catalyst Brick
Diesel Particulate
Filter
1D > 0D : it can be 10 to 50 times faster.
0D or 1D

6. Kinetics Specification
GlobalReactions Template

7. 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.

8. 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

9. Generation of BC for Standalone AT Models
EngCylEmisMaps (from Test cell)
SpeciesSampler

10. To AT Group SpeciesSampler Output: Pressure Concentrations Temperature
Flow Rate

11. An standalone Model for Catalyst Domain Experts
SpeciesSampler or
Experimental Data
CatalystBrick
Kinetics

12. Examples and Applications

13. 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

14. Deep Bed Filtration/Pressure Drop
Deep-Bed Filtration Model
Study deep bed filtration using theories
of uniform spherical collectors
and Brownian diffusion.

15. 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.

16. Experimental Validation: with an Uncoated EX-80
Symbols: measurements as Fig. 5 in SAE ;
Lines: predictions.

17. Experimental Validations: with an Coated CCRT
Symbols: measurements as Figs. 5&6 in SAE ;
Lines: predictions.

18. Experimental Validation: Active Regeneration by Fuel Injection
Symbols: measurements as Figs. 8&A.2 in SAE ;
Lines: predictions.

19. Kinetics Templates

20. 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

21. 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

22. SurfaceReactions Template
All relevant features of GlobalReactions Template
Coverage calculation
Supports storage and arbitrary functions of coverage in the rate specification

23. 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.

24. Building a SCR Model (Cont.)
Step 3: Input global kinetics to a chemistry template and link
it to flow object SCR-01
Global kinetics

25. 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.

26. Building a SCR Model (Cont.)
Step 5: Unit model testing, calibration and validation

27. Building a SCR Model (Cont.)
Step 6: Add subsytems

28. 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

29. Building a SCR Model - Advanced
User can optionally account for NH3 storage using
‘SurfaceReactions’ template:

30. Building a SCR Model - Advanced
Desorption: S(NH3) -> NH3 + S
Steady State
Absorption: NH3 + S -> S(NH3)

31. Building a SCR Model - Advanced
User can optionally account for NH3 storage using ‘SurfaceReactions’ template:

32. 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

33. 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).

34. DOC + LNT Example

35. DOC + LNT Example

36. Lean Operation 0-10s Rich Operation 10-20s
DOC + LNT Example
Lean Operation 0-10s Rich Operation 10-20s

37. Kinetic Parameter Identification

38. 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

39. Kinetics of 3-Way Catalyst
Global Reaction Scheme
Individual Production Rates:
Inhibition Terms:
K expressions for near equilibrium behavior:

40. 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)

41. TWC: Experimental Inlet Conditions
Minor species inlet mole fractions
Inlet exhaust temperature and mass flow rate

42. Test Rig Model
Global Reactions
used to define
chemical kinetics

43. Error = Sum{(measured-predicted)^2}
Test Rig Model (Cont.)
Error = Sum{(measured-predicted)^2}
User Defined
Error Function
Input for
Measured Data

44. DOE Sensitivity Study
Built-in DOE tools is used to perform sensitivity study
Latin Hypercube partial factorial

45. DOE Sensitivity Results
Sensitivities
Error Function value of 200 experiments

46. DOE Sensitivity Study
Discovered that the following 3 equations most significantly affected results:
R1 and R4 most sensitive
R2 also sensitive R1 R4 R2

47. 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

48. System Integration and Simulation

49. Integrated Model of Engine, Vehicle and DPF Systems

50. Typical Results of System Simulation

51. 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)

52. 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

53. 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

54. Thank You!
10th DOE Crosscut Workshop on Lean Emissions Reduction Simulation May 1st - 3rd, 2007