TY - CHAP A1 - Mauß, Fabian A1 - Pasternak, Michal A1 - Bensler, H. T1 - Diesel Engine Cycle Simulation with Reduced Set of Modeling Parameter Based on Detailed Kinetics Y1 - 2009 ER - TY - GEN A1 - Tuner, Martin A1 - Pasternak, Michal A1 - Mauß, Fabian A1 - Bensler, H. T1 - A PDF-Based Model for Full Cycle Simulation of Direct Injected Engines T2 - SAE Technical Papers N2 - In one-dimensional engine simulation programs the simulation of engine performance is mostly done by parameter fitting in order to match simulations with experimental data. The extensive fitting procedure is especially needed for emissions formation - CO, HC, NO, soot - simulations. An alternative to this approach is, to calculate the emissions based on detailed kinetic models. This however demands that the in-cylinder combustion-flow interaction can be modeled accurately, and that the CPU time needed for the model is still acceptable. PDF based stochastic reactor models offer one possible solution. They usually introduce only one (time dependent) parameter - the mixing time - to model the influence of flow on the chemistry. They offer the prediction of the heat release, together with all emission formation, if the optimum mixing time is given. Hence parameter fitting for a number of kinetic processes, that depend also on the in cylinder flow conditions is replaced by a single parameter fitting for the turbulent mixing time. In this work a PDF based model was implemented and coupled to the full cycle engine simulation tool, WAVE, and calculations were compared to engine experiments. Modeling results show good agreement with the experiments and show that PDF based Dl models can be used for fast and accurate simulation of Dl engine emissions and performance. Y1 - 2008 SN - 0096-5170 SN - 0148-7191 IS - 2008-01-1606 ER - TY - GEN A1 - Pasternak, Michal A1 - Nakov, Galin A1 - Mauß, Fabian A1 - Lehtiniemi, Harry T1 - Aspects of 0D and 3D Modeling of Soot Formation for Diesel Engines T2 - Combustion Science and Technology Y1 - 2014 U6 - https://doi.org/10.1080/00102202.2014.935213 SN - 1563-521X SN - 0010-2202 VL - 186 IS - 10-11 SP - 1517 EP - 1535 ER - TY - CHAP A1 - Pasternak, Michal A1 - Mauß, Fabian ED - Leipertz, Alfred T1 - Simulation von Kraftstoffeffekten unter Dieselmotorischen Bedingungen mittels eines OD Kraftstoff-Versuchsstandes T2 - Motorische Verbrennung, aktuelle Probleme und moderne Lösungsansätze XI. Tagung im Haus der Technik e.V., Ludwigsburg, 14./15. März 2013 Y1 - 2013 SN - 978-3-931901-87-5 SP - 337 EP - 346 PB - ESYTEC Energie- u. Systemtechnik CY - Erlangen ER - TY - CHAP A1 - Pasternak, Michal A1 - Mauß, Fabian ED - Sens, Marc ED - Baar, Roland T1 - Aspects of Diesel Engine In-Cylinder Processes Simulation Using 0D Stochastic Reactor Model T2 - Engine processes Y1 - 2013 SN - 978-3-8169-3222-2 SP - 139 PB - Expert Verlag CY - Renningen ER - TY - GEN A1 - Pasternak, Michal A1 - Mauß, Fabian A1 - Sens, Marc A1 - Riess, Michael A1 - Benz, Andreas A1 - Stapf, Karl Georg T1 - Gasoline Engine Simulations Using a Zero-Dimensional Spark Ignition Stochastic Reactor Model and Three-Dimensional Computational Fluid Dynamics Engine Model T2 - International Journal of Engine Research N2 - A simulation process for spark ignition gasoline engines is proposed. The process is based on a zero-dimensional spark ignition stochastic reactor model and three-dimensional computational fluid dynamics of the cold in-cylinder flow. The cold flow simulations are carried out to analyse changes in the turbulent kinetic energy and its dissipation. From this analysis, the volume-averaged turbulent mixing time can be estimated that is a main input parameter for the spark ignition stochastic reactor model. The spark ignition stochastic reactor model is used to simulate combustion progress and to analyse auto-ignition tendency in the end-gas zone based on the detailed reaction kinetics. The presented engineering process bridges the gap between three-dimensional and zero-dimensional models and is applicable to various engine concepts, such as, port-injected and direct injection engines, with single and multiple spark plug technology. The modelling enables predicting combustion effects and estimating the risk of knock occurrence at different operating points or new engine concepts for which limited experimental data are available. KW - Spark Ignition Engine, Engine Knock, Stochastic Reactor Model Y1 - 2016 U6 - https://doi.org/10.1177/1468087415599859 SN - 1468-0874 VL - 17 IS - 1 SP - 76 EP - 85 ER - TY - GEN A1 - Pasternak, Michal A1 - Mauß, Fabian A1 - Xavier, Fabio A1 - Riess, Michael A1 - Sens, Marc A1 - Benz, Andreas T1 - 0D/3D Simulations of Combustion in Gasoline Engines Operated with Multiple Spark Plug Technology T2 - SAE Technical Papers N2 - A simulation method is presented for the analysis of combustion in spark ignition (SI) engines operated at elevated exhaust gas recirculation (EGR) level and employing multiple spark plug technology. The modeling is based on a zero-dimensional (0D) stochastic reactor model for SI engines (SI-SRM). The model is built on a probability density function (PDF) approach for turbulent reactive flows that enables for detailed chemistry consideration. Calculations were carried out for one, two, and three spark plugs. Capability of the SI-SRM to simulate engines with multiple spark plug (multiple ignitions) systems has been verified by comparison to the results from a three-dimensional (3D) computational fluid dynamics (CFD) model. Numerical simulations were carried for part load operating points with 12.5%, 20%, and 25% of EGR. At high load, the engine was operated at knock limit with 0%, and 20% of EGR and different inlet valve closure timing. The quasi-3D treatment of combustion chamber geometry and the spherical flame propagation by the 0D SI-SRM enabled for estimating the impact of number of spark plugs on the combustion progress and the risk of knock occurrence. Application of three spark plugs shortened significantly the combustion process. When the engine was operated at knock limit and with 20% EGR, combustion duration was similar to that of engine operation without EGR and with one spark plug. Overall, the results presented demonstrate that this method has the potential to support early stages of engine development with limited experimental data available. KW - Spark Igniton Engine, Multiple Spark Plug Technology, Stochastic Reactor Modeling Y1 - 2015 U6 - https://doi.org/10.4271/2015-01-1243 SN - 0148-7191 SN - 0096-5170 IS - 2015-01-1243 ER - TY - GEN A1 - Matrisciano, Andrea A1 - Borg, Anders A1 - Perlman, Cathleen A1 - Lehtiniemi, Harry A1 - Pasternak, Michal A1 - Mauß, Fabian T1 - Soot Source Term Tabulation Strategy for Diesel Engine Simulations with SRM T2 - SAE Technical Papers N2 - In this work a soot source term tabulation strategy for soot predictions under Diesel engine conditions within the zero-dimensional Direct Injection Stochastic Reactor Model (DI-SRM) framework is presented. The DI-SRM accounts for detailed chemistry, in-homogeneities in the combustion chamber and turbulence-chemistry interactions. The existing implementation [1] was extended with a framework facilitating the use of tabulated soot source terms. The implementation allows now for using soot source terms provided by an online chemistry calculation, and for the use of a pre-calculated flamelet soot source term library. Diesel engine calculations were performed using the same detailed kinetic soot model in both configurations. The chemical mechanism for n-heptane used in this work is taken from Zeuch et al. [2] and consists of 121 species and 973 reactions including PAH and thermal NO chemistry. The engine case presented in [1] is used also for this work. The case is a single-injection part-load passenger car Diesel engine with 27 % EGR fueled with regular Diesel fuel. The two different approaches are analyzed and a detailed comparison is presented for the different soot processes globally and in the mixture fraction space. The contribution of the work presented in this paper is that a method which allows for a direct comparison of soot source terms - calculated online or retrieved from a flamelet table - without any change in the simulation setup has been developed within the SRM framework. It is a unique tool for model development. Our analysis supports our previous conclusion [1] that flamelet soot source terms libraries can be used for multi-dimensional modeling of soot formation in Diesel engines. KW - Diesel Engine, Stochastic Reactor Modeling, Particlulate Matter Y1 - 2015 U6 - https://doi.org/10.4271/2015-24-2400 SN - 0148-7191 SN - 0096-5170 IS - 2015-24-2400 SP - 1 EP - 15 ER - TY - CHAP A1 - Seidel, Lars A1 - Klauer, Christian A1 - Pasternak, Michal A1 - Matrisciano, Andrea A1 - Netzer, Corinna A1 - Hilbig, Martin A1 - Mauß, Fabian T1 - Systematic Mechanism Reduction for Engine Applications T2 - 5th International Workshop on Model Reduction in Reacting Flows, Lübbenau, 2015 N2 - In this work we apply various concepts of mechanism reduction with a PDF based method for species profile conservation. The reduction process is kept time efficient by only using 0D and 1D reactors. To account for the expansion phase in internal combustion engines a stochastic engine tool is used to validate the reduction steps. KW - Combustion, Mechanism Reduction Y1 - 2015 UR - www.modelreduction.net UR - http://modelreduction.net/wp-content/uploads/2015/07/5th_IWMRRF_2015.pdf ER - TY - CHAP A1 - Pasternak, Michal A1 - Mauß, Fabian A1 - Matrisciano, Andrea ED - Sens, Marc ED - Baar, Roland T1 - Diesel Engine Performance Mapping Using Stochastic Reactor Model T2 - Proceedings of the 2nd Conference on Engine Processes, July 2–3, 2015, Berlin, Germany KW - Diesel Engine Performance Mapping Y1 - 2015 SN - 978-3-7983-2768-9 SP - 217 EP - 232 PB - Tech. Univ., Universitätsverlag CY - Berlin ER - TY - GEN A1 - Matrisciano, Andrea A1 - Pasternak, Michal A1 - Wang, Xiaoxiao A1 - Antoshkiv, Oleksiy A1 - Mauß, Fabian A1 - Berg, Peter T1 - On the Performance of Biodiesel Blends – Experimental Data and Simulations Using a Stochastic Fuel Test Bench T2 - SAE Technical Papers Y1 - 2014 U6 - https://doi.org/10.4271/2014-01-1115 SN - 0148-7191 SN - 0096-5170 IS - 2014-01-1115 SP - 1 EP - 8 ER - TY - CHAP A1 - Matrisciano, Andrea A1 - Borg, Anders A1 - Perlman, Cathleen A1 - Pasternak, Michal A1 - Seidel, Lars A1 - Netzer, Corinna A1 - Mauß, Fabian A1 - Lehtiniemi, Harry T1 - Simulation of DI-Diesel combustion using tabulated chemistry approach T2 - 1st Conference on Combustion Processes in Marine and Automotive Engines, 7th - 8th June 2016, Lund, Schweden KW - Simulation of DI-Diesel Y1 - 2016 UR - http://ecco-mate.eu/images/Training%20events/LUND/ECCO-MATE_C1_Proceedings.pdf SP - 44 EP - 47 ER - TY - CHAP A1 - Seidel, Lars A1 - Netzer, Corinna A1 - Hilbig, Martin A1 - Mauß, Fabian A1 - Klauer, Christian A1 - Pasternak, Michal A1 - Matrisciano, Andrea T1 - Systematic Reduction of Detailed Chemical Reaction Mechanisms for Engine Applications T2 - ASME 2016 Internal Combustion Engine Division Fall Technical Conference Greenville, South Carolina, USA, October 9–12, 2016 N2 - In this work we apply a sequence of concepts for mechanism reduction on one reaction mechanism including novel quality control. We introduce a moment based accuracy rating method for species profiles. The concept is used for a necessity based mechanism reduction utilizing 0D reactors. Thereafter a stochastic reactor model (SRM) for internal combustion engines is applied to control the quality of the reduced reaction mechanism during the expansion phase of the engine. This phase is sensitive on engine out emissions, and is often not considered in mechanism reduction work. The proposed process allows to compile highly reduced reaction schemes for CFD application for internal combustion engine simulations. It is demonstrated that the resulting reduced mechanisms predict combustion and emission formation in engines with accuracies comparable to the original detailed scheme. KW - Systematic Reduction KW - Chemical Reaction Mechanismus for Engine Applications Y1 - 2016 SN - 978-0-7918-5050-3 N1 - Paper No. ICEF2016-9304 PB - The American Society of Mechanical Engineers CY - New York, N.Y. ER - TY - THES A1 - Pasternak, Michal T1 - Simulation of the Diesel Engine Combustion Process Using the Stochastic Reactor Model KW - Diesel engine KW - Non-premixed combustion KW - Stochastic reactor model KW - Probability density function method KW - Numerical engine simulation KW - Turbulence-chemistry interactions Y1 - 2016 SN - 978-3-8325-4310-5 PB - Logos Verlag Berlin CY - Berlin ER - TY - GEN A1 - Netzer, Corinna A1 - Seidel, Lars A1 - Pasternak, Michal A1 - Klauer, Christian A1 - Perlman, Cathleen A1 - Ravet, Frédéric A1 - Mauß, Fabian T1 - Engine Knock Prediction and Evaluation Based on Detonation Theory Using a Quasi-Dimensional Stochastic Reactor Mode T2 - SAE technical paper KW - Engine Knock Prediction and Evaluation Based Y1 - 2017 U6 - https://doi.org/10.4271/2017-01-0538 SN - 0096-5170 SN - 0148-7191 IS - 2017-01-0538 SP - 11 Seiten ER - TY - CHAP A1 - Netzer, Corinna A1 - Seidel, Lars A1 - Pasternak, Michal A1 - Mauß, Fabian A1 - Lehtiniemi, Harry A1 - Perlman, Cathleen A1 - Ravet, Frédéric ED - Leipertz, Alfred ED - Fröba, Andreas Paul T1 - 3D CFD Engine Knock Predication and Evaluation Based on Detailed Chemistry and Detonation Theory T2 - Motorische Verbrennung : aktuelle Probleme und moderne Lösungsansätze, XIII. Tagung im Haus der Technik Ludwigsburg, 16.-17. März 2017 KW - 3D CFD Engine Knock Y1 - 2017 SN - 978-3-945806-08-1 PB - ESYTEC Energie- und Systemtechnik GmbH CY - Erlangen ER - TY - CHAP A1 - Netzer, Corinna A1 - Seidel, Lars A1 - Pasternak, Michal A1 - Klauer, Christian A1 - Perlman, Cathleen A1 - Ravet, Frédéric A1 - Mauß, Fabian T1 - Impact of Gasoline Octane Rating on Engine Knock using Detailed Chemistry and a Quasi-dimensional Stochastic Reaktior Model T2 - Digital Proceedings of the 8th European Combustion Meeting (ECM 2017), Dubrovnik, Croatia Y1 - 2017 UR - https://www.researchgate.net/publication/319059022 SP - 493 EP - 498 ER - TY - GEN A1 - Pasternak, Michal A1 - Mauß, Fabian A1 - Klauer, Christian A1 - Matrisciano, Andrea T1 - Diesel engine performance mapping using a parametrized mixing time model T2 - International Journal of Engine Research KW - Diesel engine performance Y1 - 2018 U6 - https://doi.org/10.1177/1468087417718115 SN - 2041-3149 SN - 1468-0874 VL - 19 IS - 2 SP - 202 EP - 213 ER - TY - CHAP A1 - Fischer, Michael A1 - Günther, Michael A1 - Berger, Carsten A1 - Troeger, Ralf A1 - Pasternak, Michal A1 - Mauß, Fabian ED - Günther, Michael ED - Sens, Marc T1 - Suppressing Knocking by Using CleanEGR – Better Fuel Economy and Lower Raw Emissions Simultaneously T2 - Knocking in Gasoline Engines, 5th International Conference, December 12-13, 2017, Berlin, Germany KW - Suppressing Knocking Y1 - 2018 SN - 978-3-319-69760-4 U6 - https://doi.org/10.1007/978-3-319-69760-4_21 SP - 384 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Pasternak, Michal A1 - Netzer, Corinna A1 - Mauß, Fabian A1 - Fischer, Michael A1 - Sens, Marc A1 - Riess, Michael ED - Günther, Michael ED - Sens, Marc T1 - Simulation of the Effects of Spark Timing and External EGR on Gasoline Combustion Under Knock-Limited Operation at High Speed and Load T2 - Knocking in Gasoline Engines, 5th International Conference, December 12-13, 2017, Berlin, Germany Y1 - 2018 SN - 978-3-319-69760-4 U6 - https://doi.org/10.1007/978-3-319-69760-4_8 SP - 121 EP - 142 PB - Springer International Publishing CY - Cham ER - TY - GEN A1 - Seidel, Lars A1 - Netzer, Corinna A1 - Hilbig, Martin A1 - Mauß, Fabian A1 - Klauer, Christian A1 - Pasternak, Michal A1 - Matrisciano, Andrea T1 - Systematic reduction of detailed chemical reaction mechanisms for engine applications T2 - Journal of Engineering for Gas Turbines and Power N2 - In this work, we apply a sequence of concepts for mechanism reduction on one reaction mechanism including novel quality control. We introduce a moment-based accuracy rating method for species profiles. The concept is used for a necessity-based mechanism reduction utilizing 0D reactors. Thereafter a stochastic reactor model for internal combustion engines is applied to control the quality of the reduced reaction mechanism during the expansion phase of the engine. This phase is sensitive on engine out emissions, and is often not considered in mechanism reduction work. The proposed process allows to compile highly reduced reaction schemes for computational fluid dynamics application for internal combustion engine simulations. It is demonstrated that the resulting reduced mechanisms predict combustion and emission formation in engines with accuracies comparable to the original detailed scheme. KW - Reaction Mechanism Reduction KW - Engine Modelling Y1 - 2017 U6 - https://doi.org/10.1115/1.4036093 SN - 1528-8919 SN - 0742-4795 VL - 139 IS - 9 SP - 091701-1 EP - 091701-9 ER - TY - CHAP A1 - Franken, Tim A1 - Netzer, Corinna A1 - Pasternak, Michal A1 - Mauß, Fabian A1 - Seidel, Lars A1 - Matrisciano, Andrea A1 - Borg, Anders A1 - Lehtiniemi, Harry A1 - Kulzer, André Casal T1 - Assessment of Water Injection in a SI Engine using a Fast Running Detailed Chemistry Based Combustion Model T2 - Symposium of Combustion Control 2018, Aachen KW - Assessment of Water Injection Y1 - 2018 UR - https://www.researchgate.net/publication/326059620 UR - http://logesoft.com/loge-16/wp-content/uploads/2018/07/2018-06-19-SCC_-1.pdf CY - Aachen ER - TY - GEN A1 - Franken, Tim A1 - Netzer, Corinna A1 - Pasternak, Michal A1 - Mauß, Fabian A1 - Seidel, Lars A1 - Matrisciano, Andrea A1 - Borg, Anders A1 - Lehtiniemi, Harry A1 - Kulzer, André Casal T1 - Simulation of Spark-Ignited Engines with Water Injection using the Stochastic Reactor Model, 37th International Symposium on Combustion Y1 - 2018 UR - https://www.researchgate.net/publication/328265636 ER - TY - GEN A1 - Netzer, Corinna A1 - Seidel, Lars A1 - Pasternak, Michal A1 - Lehtiniemi, Harry A1 - Perlman, Cathleen A1 - Ravet, Frédéric A1 - Mauß, Fabian T1 - Three-dimensional computational fluid dynamics engine knock prediction and evaluation based on detailed chemistry and detonation theory T2 - International Journal of Engine Research N2 - Engine knock is an important phenomenon that needs consideration in the development of gasoline-fueled engines. In our days, this development is supported using numerical simulation tools to further understand and predict in-cylinder processes. In this work, a model tool chain which uses a detailed chemical reaction scheme is proposed to predict the auto-ignition behavior of fuels with different octane ratings and to evaluate the transition from harmless auto-ignitive deflagration to knocking combustion. In our method, the auto-ignition characteristics and the emissions are calculated using a gasoline surrogate reaction scheme containing pathways for oxidation of ethanol, toluene, n-heptane, iso-octane and their mixtures. The combustion is predicted using a combination of the G-equation based flame propagation model utilizing tabulated laminar flame speeds and well-stirred reactors in the burned and … KW - Engine knock is an important phenomenon Y1 - 2018 U6 - https://doi.org/10.1177/1468087417740271 SN - 1468-0874 SN - 2041-3149 VL - 19 IS - 1 SP - 33 EP - 44 ER - TY - GEN A1 - Netzer, Corinna A1 - Pasternak, Michal A1 - Seidel, Lars A1 - Ravet, Frédéric A1 - Mauß, Fabian T1 - Computationally efficient prediction of cycle-to-cycle variations in spark-ignition engines T2 - International Journal of Engine Research N2 - Cycle-to-cycle variations are important to consider in the development of spark-ignition engines to further increase fuel conversion efficiency. Direct numerical simulation and large eddy simulation can predict the stochastics of flows and therefore cycle-to-cycle variations. However, the computational costs are too high for engineering purposes if detailed chemistry is applied. Detailed chemistry can predict the fuels’ tendency to auto-ignite for different octane ratings as well as locally changing thermodynamic and chemical conditions which is a prerequisite for the analysis of knocking combustion. In this work, the joint use of unsteady Reynolds-averaged Navier–Stokes simulations for the analysis of the average engine cycle and the spark-ignition stochastic reactor model for the analysis of cycle-to-cycle variations is proposed. Thanks to the stochastic approach for the modeling of mixing and heat transfer, the spark-ignition stochastic reactor model can mimic the randomness of turbulent flows that is missing in the Reynolds-averaged Navier–Stokes modeling framework. The capability to predict cycle-to-cycle variations by the spark-ignition stochastic reactor model is extended by imposing two probability density functions. The probability density function for the scalar mixing time constant introduces a variation in the turbulent mixing time that is extracted from the unsteady Reynolds-averaged Navier–Stokes simulations and leads to variations in the overall mixing process. The probability density function for the inflammation time accounts for the delay or advancement of the early flame development. The combination of unsteady Reynolds-averaged Navier–Stokes and spark-ignition stochastic reactor model enables one to predict cycle-to-cycle variations using detailed chemistry in a fraction of computational time needed for a single large eddy simulation cycle. Y1 - 2020 U6 - https://doi.org/10.1177/1468087419856493 SN - 2041-3149 SN - 1468-0874 VL - 21 IS - 4 SP - 649 EP - 663 ER - TY - GEN A1 - Franken, Tim A1 - Netzer, Corinna A1 - Mauß, Fabian A1 - Pasternak, Michal A1 - Seidel, Lars A1 - Borg, Anders A1 - Lehtiniemi, Harry A1 - Matrisciano, Andrea A1 - Kulzer, André Casal T1 - Multi-objective optimization of water injection in spark-ignition engines using the stochastic reactor model with tabulated chemistry T2 - International Journal of Engine Research N2 - Water injection is investigated for turbocharged spark-ignition engines to reduce knock probability and enable higher engine efficiency. The novel approach of this work is the development of a simulation-based optimization process combining the advantages of detailed chemistry, the stochastic reactor model and genetic optimization to assess water injection. The fast running quasi-dimensional stochastic reactor model with tabulated chemistry accounts for water effects on laminar flame speed and combustion chemistry. The stochastic reactor model is coupled with the Non-dominated Sorting Genetic Algorithm to find an optimum set of operating conditions for high engine efficiency. Subsequently, the feasibility of the simulation-based optimization process is tested for a three-dimensional computational fluid dynamic numerical test case. The newly proposed optimization method predicts a trade-off between fuel efficiency and low knock probability, which highlights the present target conflict for spark-ignition engine development. Overall, the optimization shows that water injection is beneficial to decrease fuel consumption and knock probability at the same time. The application of the fast running quasi-dimensional stochastic reactor model allows to run large optimization problems with low computational costs. The incorporation with the Non-dominated Sorting Genetic Algorithm shows a well performing multi-objective optimization and an optimized set of engine operating parameters with water injection and high compression ratio is found. KW - Water Injection KW - Genetic Optimization KW - Spark Ignition Engine KW - Stochastic Reactor Model KW - Detailed Chemistry Y1 - 2019 UR - https://journals.sagepub.com/doi/full/10.1177/1468087419857602 U6 - https://doi.org/10.1177/1468087419857602 SN - 2041-3149 VL - 20 IS - 10 SP - 1089 EP - 1100 ER - TY - GEN A1 - Franken, Tim A1 - Matrisciano, Andrea A1 - Sari, Rafael A1 - Robles, Alvaro Fogue A1 - Monsalve-Serrano, Javier A1 - Pintor, Dario Lopez A1 - Pasternak, Michal A1 - Garcia, Antonio A1 - Mauß, Fabian T1 - Modeling of Reactivity Controlled Compression Ignition Combustion Using a Stochastic Reactor Model Coupled with Detailed Chemistry T2 - SAE technical papers : 15th International Conference on Engines & Vehicles N2 - Advanced combustion concepts such as reactivity controlled compression ignition (RCCI) have been proven to be capable of fundamentally improve the conventional Diesel combustion by mitigating or avoiding the soot-NOx trade-off, while delivering comparable or better thermal efficiency. To further facilitate the development of the RCCI technology, a robust and possibly computationally efficient simulation framework is needed. While many successful studies have been published using 3D-CFD coupled with detailed combustion chemistry solvers, the maturity level of the 0D/1D based software solution offerings is relatively limited. The close interaction between physical and chemical processes challenges the development of predictive numerical tools, particularly when spatial information is not available. The present work discusses a novel stochastic reactor model (SRM) based modeling framework capable of predicting the combustion process and the emission formation in a heavy-duty engine running under RCCI combustion mode. The combination of physical turbulence models, detailed emission formation sub-models and stateof-the-art chemical kinetic mechanisms enables the model to be computationally inexpensive compared to the 3D-CFD approaches. A chemical kinetic mechanism composed of 248 species and 1428 reactions was used to describe the oxidation of gasoline and diesel using a primary reference fuel (PRF)mixture and n-heptane, respectively. The model is compared to operating conditions from a single-cylinder research engine featuring different loads, speeds, EGR and gasoline fuel fractions. The model was found to be capable of reproducing the combustion phasing as well as the emission trends measured on the test bench, at some extent. The proposed modeling approach represents a promising basis towards establishing a comprehensive modeling framework capable of simulating transient operation as well as fuel property sweeps with acceptable accuracy. KW - Stochastic Reactor Models KW - RCCI KW - Chemical Kinetics KW - Low Temperature Combustion Y1 - 2021 UR - https://www.sae.org/publications/technical-papers/content/2021-24-0014/ U6 - https://doi.org/10.4271/2021-24-0014 SN - 0148-7191 SN - 2688-3627 ER - TY - GEN A1 - Picerno, Mario A1 - Lee, Sung-Yong A1 - Pasternak, Michal A1 - Siddareddy, Reddy Babu A1 - Franken, Tim A1 - Mauß, Fabian A1 - Andert, Jakob T1 - Real-Time Emission Prediction with Detailed Chemistry under Transient Conditions for Hardware-in-the-Loop Simulations T2 - Energies N2 - The increasing requirements to further reduce pollutant emissions, particularly with regard to the upcoming Euro 7 (EU7) legislation, cause further technical and economic challenges for the development of internal combustion engines. All the emission reduction technologies lead to an increasing complexity not only of the hardware, but also of the control functions to be deployed in engine control units (ECUs). Virtualization has become a necessity in the development process in order to be able to handle the increasing complexity. The virtual development and calibration of ECUs using hardware-in-the-loop (HiL) systems with accurate engine models is an effective method to achieve cost and quality targets. In particular, the selection of the best-practice engine model to fulfil accuracy and time targets is essential to success. In this context, this paper presents a physically- and chemically-based stochastic reactor model (SRM) with tabulated chemistry for the prediction of engine raw emissions for real-time (RT) applications. First, an efficient approach for a time-optimal parametrization of the models in steady-state conditions is developed. The co-simulation of both engine model domains is then established via a functional mock-up interface (FMI) and deployed to a simulation platform. Finally, the proposed RT platform demonstrates its prediction and extrapolation capabilities in transient driving scenarios. A comparative evaluation with engine test dynamometer and vehicle measurement data from worldwide harmonized light vehicles test cycle (WLTC) and real driving emissions (RDE) tests depicts the accuracy of the platform in terms of fuel consumption (within 4% deviation in the WLTC cycle) as well as NOx and soot emissions (both within 20%). KW - hardware-in-the-loop KW - virtual calibration KW - diesel powertrain KW - tabulated chemistry Y1 - 2022 U6 - https://doi.org/10.3390/en15010261 SN - 1996-1073 VL - 15 IS - 1 SP - 1 EP - 21 ER - TY - GEN A1 - Siddareddy, Reddy Babu A1 - Franken, Tim A1 - Pasternak, Michal A1 - Leon de Syniawa, Larisa A1 - Oder, Johannes A1 - Rottengruber, Hermann A1 - Mauß, Fabian T1 - Real-Time Simulation of CNG Engine and After-Treatment System Cold Start. Part 1: Transient Engine-Out Emission Prediction Using a Stochastic Reactor Model T2 - SAE Technical Paper N2 - During cold start of natural gas engines, increased methane and formaldehyde emissions can be released due to flame quenching on cold cylinder walls, misfiring and the catalyst not being fully active at low temperatures. Euro 6 legislation does not regulate methane and formaldehyde emissions. New limits for these two pollutants have been proposed by CLOVE consortium for Euro 7 scenarios. These proposals indicate tougher requirements for aftertreatment systems of natural gas engines. In the present study, a zero-dimensional model for real-time engine-out emission prediction for transient engine cold start is presented. The model incorporates the stochastic reactor model for spark ignition engines and tabulated chemistry. The tabulated chemistry approach allows to account for the physical and chemical properties of natural gas fuels in detail by using a-priori generated laminar flame speed and combustion chemistry look-up tables. The turbulence-chemistry interaction within the combustion chamber is predicted using a K-k turbulence model. The optimum turbulence model parameters are trained by matching the experimental cylinder pressure and engine-out emissions of nine steady-state operating points. Subsequently, the trained engine model is applied for predicting engine-out emissions of a WLTP passenger car engine cold start. The predicted engine-out emissions comprise nitrogen oxide, carbon monoxide, carbon dioxide, unburnt methane, formaldehyde, and hydrogen. The simulation results are validated by comparing to transient engine measurements at different ambient temperatures (-7°C, 0°C, 8°C and 20°C). Additionally, the sensitivity of engine-out emissions towards air-fuel-ratio (λ=1.0 and λ=1.3) and natural gas quality (H-Gas and L-Gas) is investigated. KW - Spark Ignition Engines KW - Gas Engines KW - Alternative Fuel Engines KW - Natural Gas KW - Nitrogen Oxides KW - Cold Start KW - Carbon Monoxide KW - Methane KW - Formaldehyde KW - Simulation KW - Stochastic Reactor Model KW - Tabulated Chemistry Y1 - 2023 U6 - https://doi.org/10.4271/2023-01-0183 SN - 2688-3627 SN - 0148-7191 ER - TY - GEN A1 - Siddareddy, Reddy Babu A1 - Franken, Tim A1 - Leon de Syniawa, Larisa A1 - Pasternak, Michal A1 - Prehn, Sascha A1 - Buchholz, Bert A1 - Mauß, Fabian T1 - Simulation of CNG Engine in Agriculture Vehicles. Part 1: Prediction of Cold Start Engine-Out Emissions Using Tabulated Chemistry and Stochastic Reactor Model T2 - SAE Technical Paper N2 - Worldwide, there is the demand to reduce harmful emissions from non-road vehicles to fulfill European Stage V+ and VI (2022, 2024) emission legislation. The rules require significant reductions in nitrogen oxides (NOx), methane (CH4) and formaldehyde (CH2O) emissions from non-road vehicles. Compressed natural gas (CNG) engines with appropriate exhaust aftertreatment systems such as threeway catalytic converter (TWC) can meet these regulations. An issue remains for reducing emissions during the engine cold start where the CNG engine and TWC yet do not reach their optimum operating conditions. The resulting complexity of engine and catalyst calibration can be efficiently supported by numerical models. Hence, it is required to develop accurate simulation models which can predict cold start emissions. This work presents a real-time engine model for transient engine-out emission prediction using tabulated chemistry for CNG. The engine model is based on a stochastic reactor model (SRM) which describes the in-cylinder processes of spark ignition (SI) engines including large-scale and lowscale turbulence, convective heat transfer, turbulent flame propagation and chemistry. Chemistry is described using a tabulated chemistry model which calculates the major exhaust gas emissions of CNG engines such as CO2, NOx, CO, CH4 and CH2O. By best practice, the engine model parameters are optimized by matching the experimental cylinder pressure and engine-out emissions from steady-state operating points. The engine model is trained for a non-road transient cycle (NRTC) cold start at 25°C ambient temperature and validated for a NRTC cold start at 10°C ambient temperature. The trained model is evaluated regarding their feasibility and accuracy predicting transient engineout emissions. KW - CNG engine KW - Cold start KW - Stochastic reactor model KW - Tabulated chemistry KW - Natural gas KW - Driving cycle Y1 - 2023 U6 - https://doi.org/10.4271/2023-24-0006 SN - 0148-7191 SN - 2688-3627 ER - TY - GEN A1 - Pasternak, Michał A1 - Siddareddy, Reddy Babu A1 - de Syniawa, Larisa León A1 - Guenther, Vivien A1 - Picerno, Mario A1 - Andert, Jakob A1 - Franken, Tim A1 - Mauss, Fabian A1 - Adamczyk, Wojciech T1 - Plant modelling of engine and aftertreatment systems for X-in-the-loop simulations with detailed chemistry T2 - CONAT 2024 International Congress of Automotive and Transport Engineering. N2 - Use of numerical simulations at early stage of engine and aftertreatment systems development helps in evaluating their different concepts and reducing the need for costly building of prototypes. In this work, we explore the feasibility of fully physical and chemical-based tool-chain for co-simulating engine in-cylinder and aftertreatment processes. Detailed gas-phase reaction kinetics and surface chemistry mechanisms are applied for the modeling of combustion, pollutants formation and aftertreatment, respectively. Engine in-cylinder performance parameters are simulated using a stochastic reactor model and multi-component fuel surrogate. The engine model is coupled with an aftertreatment model capable of simulating diesel oxidation catalyst (DOC), selective catalytic reduction catalyst, lean NOx trap, ammonia slip catalyst, and three-way catalyst. Both the engine and aftertreatment models are embedded within the Simulink framework. They work in co-simulation and are coupled using Functional Mock-up Interface (FMI) technology. The coupled framework acts as a virtual test bench that is developed given its application for X-in-the-Loop (XiL) simulations. The framework can be applied to engine steady state or transient operating conditions. Here, exemplary calculations are performed using a Model-in-the-Loop (MiL) approach. Simulations are conducted under transient conditions of Worldwide Harmonized Light Vehicle Test Cycle for a compression ignition engine coupled with a DOC. The presented framework is considered a first step towards complex engine plant modeling using detailed chemistry for the virtualization of the development of engine, fuels and aftertreatment systems. Y1 - 2024 SN - 978-3-031-77626-7 U6 - https://doi.org/10.1007/978-3-031-77627-4_14 SP - 151 EP - 163 PB - Springer Nature Switzerland CY - Cham ER - TY - GEN A1 - Siddareddy, Reddy Babu A1 - Pasternak, Michał A1 - de Syniawa, Larisa León A1 - Guenther, Vivien A1 - Seidel, Lars A1 - Mauss, Fabian A1 - Przybyła, Grzegorz A1 - Adamczyk, Wojciech T1 - Simulations of the SCR catalyst in ammonia-biodiesel fuelled CI engine using virtual test bench with detailed chemistry T2 - Renewable energy N2 - The use of ammonia as an alternative fuel in the automotive industry is not yet fully established. Further research and development are required to account for both engine and aftertreatment systems, as well as their integration and control to ensure the most efficient use of ammonia. In this work, we present a fully physics and chemistry-based toolchain for co-simulating an ammonia-biodiesel fuelled compression ignition engine with a selective catalytic reduction catalyst. The investigations refer to experimental data from a single-cylinder research engine. This is a direct injection engine that was retrofitted to run on ammonia and biodiesel, the latter acting as a combustion promoter. Engine in-cylinder processes were simulated using a stochastic reactor model. Detailed gas phase chemistry is used to simulate the combustion process and pollutants formation. The catalyst model employs detailed surface chemistry that is trained using available data from literature. Eventually, the co-simulation toolchain was applied to investigate numerically the impact of the properties of the catalyst on ammonia reduction under engine-relevant operating conditions KW - Ammonia combustion KW - Selective reduction catalyst KW - Stochastic reactor model KW - Detailed chemistry KW - Exhaust emissions Y1 - 2025 U6 - https://doi.org/10.1016/j.renene.2025.123169 SN - 0960-1481 VL - 251 SP - 1 EP - 12 PB - Elsevier BV CY - Amsterdam ER -