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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 -