An automated approach to derive combustionand NOx-models for GT-POWER simulations

Transcription

1 An automated approach to derive combustionand NOx-models for GT-POWER simulations Dr.-Ing. Jan Boyde, Dr.-Ing. Claus-Oliver Schmalzing

2 Outline Motivation Automated cylinder pressure analysis Generation of CombRate Profile Dependency models Generation of NOx-models Comparison with measurement data Outlook Seite 2

3 Motivation Multi-cylinder GT-POWER models need reliable combustion and emission models to enable Efficiency forecast Support turbocharger design Support engine parts + valve train design Identification of emission concepts To derive reliable combustion and emission models the analysis of a large number of test bed data is required. Seite 3

4 Motivation for automation Challenge: Converting measurement data into GT-usable form and setting-up models for parameter identification for the desired combustion and NOx-models Time consuming to analyse and to convert test bed data into GT-usable data Generating and entering input data into the parameter identification models is a tedious task Manually performing the above tasks is error prone through typing errors and mixing-up of files and data Automate cylinder pressure analysis and combustion and emission model parameter identification Seite 4

5 Automated cylinder pressure analysis Workflow Read stationary data, e.g. lambda, stoichiometric air-fuel ratio from measurement file and write data to parameter file for single cylinder model Read instationary data, e.g. pressure curve of cylinder and write data into.txt files for simulation Perform TPA (Three-pressure analysis) with advanced optimizer via command prompt Independent variables: Port-Temperature + In- Cylinder Convection Multiplier Dependent variable: Difference between measured and simulated indicated mean effective pressure Save combustion profile and TPA.gdx file Test bed GT TPA Single Cylinder Model Burn rate Seite 5

6 Automated cylinder pressure analysis Model Set-up Test Bed Inlet Piping External Subassembly pointing to respective cylinder design Increases reusability Test Bed Outlet Piping Seite 6

7 Generation of CombRate Profile Dependency combustion models Advantage of CombRate Profile Dependency combustion models: In particular for stationary investigations CombRate models derived from measurements are more accurate than empirical combustion models. Challenge: Measured cylinder pressure profiles are usually not present for the entire engine operation range. For scattered burn rate data, no interpolation method is available within GT: Script in MatLab to create finer grid within experimental space with interpolation of burn-rate for inner grid points Automated generation of MultiDMapofTables object for burn rates and MultiDGridData for combustion efficiency Seite 7

8 Lambda [-] dq [-] Generation of CombRate Profile Dependency combustion models Approach for setting up the grid for the CombRate Profile Dependency combustion model: CombRates are derived for the measurement data points through the previously described TPA Interpolation of CombRates within experimental space for inner grid points Measurement Data BoC=25.4 Lambda=1.82 Measurement Data BoC=23.3 Lambda=1.80 Interpolated Data BoC=24.8 Lambda= [ CA] For grid points outside of the experimental space the nearest CombRate is used 1 2 Measurement Data Grid for CombRate Profile Dependency Seite BoC [ CA] -10 0

9 Generation of CombRate Profile Dependency combustion models How to automate the model set-up process Make use of the html structure of GT-SUITE models CombRate object has a well-defined structure Use MatLab script to create CombRate objects within an empty GT-Model Use MatLab script to create MultiDMapofTables object and set-up the right grid points and references to the CombRate objects Use MatLab to create RLTDependenceMulti object for combustion efficiency look-up Leads to a useable CombRate combustion model which can be copied to any engine model Extract from CombRate object in.gtm file Extract from MultiDMapofTables object in.gtm file Seite 9

10 General advise for automated modification HTML structure of GT-Models allows nearly every possible modification: Switch on/off of optimizer with a script (currently not possible through a parameter within GT) Add objects (e.g. CombRate-object) Connect objects (e.g. for automated model generation) Identification of the necessary text lines for modification: Save.gtm file with and without e.g. object which should be added Compare.gtm files with suitable software and identify the changes in the text Modification can then be automated with any kind of programming language Seite 10

11 Generation of NOx-Models Approach: Reutilisation of TPA model with NOx-Rate multiplier and NOx-Activation energy multiplier as independent variables of the advanced optimizer Use parameter array files to pass input data from the measurements to the model or write casesetup data directly to the.gtm file Copy the CombRate Profile Dependency model to the NOx parameter identification model Optimize with respect to minimisation of the difference between measured NOx concentration and simulated NOx concentration Identification of NOx-model parameter NOx-model parameter N2 Oxidation Rate Multiplie r N2 Oxidation Activation Energy Multiplier Seite 11

12 Pressure [bar] Comparison with measurement data Comparison of TPA model with CombRate Dependency Profile model + NOx-model with BoC = CA Lambda = 1.50 Quantity Measurement DVA CombRate Profile Dependency Model NOx [ppm] % Fuel Burned [ CA] Burned Fuel Fraction [-] Indicated Efficiency [%] Measurement DVA CombRate [ CA] Very satisfying agreement to measurement data Same agreement is achieved within the entire experimental space Seite 12

13 Conclusion A TPA is automated to derive combustion rate profiles from measurement data Combustion rate profiles are interpolated on a finer grid and the resulting interpolated combustion rate profiles are compiled into a CombRate combustion model with profile dependency A fraction of fuel burned look-up based on measurement data is created in the form of a RLTDependenceMulti A NOx-model is calibrated with the derived combustion model Comparison with measurement data shows good agreement in the entire experimental space Seite 13

14 Thank you very much for your attention. Seite 14