LOGE AB

United States
United States
SEARCH FILTERS
Time filter
Source Type

Franken T.,Ford Motor Company | Sommerhoff A.,Ford Motor Company | Willems W.,Ford Motor Company | Matrisciano A.,Chalmers University of Technology | And 4 more authors.
SAE Technical Papers | Year: 2017

Today numerical models are a major part of the diesel engine development. They are applied during several stages of the development process to perform extensive parameter studies and to investigate flow and combustion phenomena in detail. The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. 0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models. This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry. The advantage of the probability density function approach compared to mean value models is its capability to account for temperature and mixture inhomogeneities. Therefore, notional particles are introduced each with its own temperature and composition. The particle condition is changed by mixing, injection, vaporization, chemical reaction and heat transfer. Mixing is modeled using the one-dimensional Euclidean minimum spanning tree mixing model, which requires the scalar mixing frequency as input. Therefore, a turbulence model is proposed to calculate the mixing time depending on turbulent kinetic energy and its dissipation. The turbulence model accounts for density, swirl, squish and injection effects on turbulent kinetic energy within the combustion chamber. Finally, the 0D stochastic reactor model is tested for 40 different operating points distributed over the whole engine map. The results show a close match of experimental heat release rate and NOx emissions. The trends of measured CO and HC concentrations are captured qualitatively. Additionally, the 0D simulation results are compared to more detailed 3D CFD combustion simulation results for three operating points differing in engine speed and load. The comparison shows that the 0D stochastic reactor model is able to capture turbulence effects on local temperature and mixture distribution, which in turn affect NOx, CO and HC emission formation. Overall, the 0D stochastic reactor model has proven its predictive capability for the investigated diesel engine and can be assigned to tasks concerning engine map simulation and parameter sweeps. Copyright © 2017 SAE International.


Netzer C.,TU Brandenburg | Seidel L.,TU Brandenburg | Pasternak M.,TU Brandenburg | Klauer C.,LOGE AB | And 3 more authors.
SAE Technical Papers | Year: 2017

Engine knock is an important phenomenon that needs consideration in the development of gasoline fueled engines. In our days, this development is supported by the use of numerical simulation tools to further understand and subsequently predict in-cylinder processes. In this work, a model tool chain based on detailed chemical and physical models 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 and emissions are calculated based on a new reaction scheme for mixtures of iso-octane, n-heptane, toluene and ethanol (Ethanol consisting Toluene Reference Fuel, ETRF). The reaction scheme is validated for a wide range of mixtures and every desired mixture of the four fuel components can be applied in the engine simulation. The engine simulations are carried out with a quasi-dimensional stochastic reactor model that allows studying cycle-to-cycle variations. A novel post-processing strategy based on the detonation theory by Bradley et al. (2012) is developed to evaluate the character and the severity of the auto-ignition event for stochastic engine models. This theory has been successfully applied to three-dimensional computational fluid dynamics simulations before by other groups (Bates et al. 2016, Robert et al. 2015). For the discussed approach, the theory is in this paper transferred to a quasi-dimensional stochastic internal combustion engine model. We suggest to use the variance of the auto-ignition severity to characterize the harmfulness of knocking operating conditions. By using the suggested tool chain, the knock limit can be predicted close to experimental findings. Fuel properties such as octane ratings can be studied. The transition from harmless deflagration to knocking combustion can be pictured, further investigated and the severity of the auto-ignition event evaluated. Copyright © 2017 SAE International.


Matrisciano A.,Chalmers University of Technology | Franken T.,Ford Motor Company | Perlman C.,LOGE AB | Borg A.,LOGE AB | And 2 more authors.
SAE Technical Papers | Year: 2017

A novel 0-D Probability Density Function (PDF) based approach for the modelling of Diesel combustion using tabulated chemistry is presented. The Direct Injection Stochastic Reactor Model (DI-SRM) by Pasternak et al. has been extended with a progress variable based framework allowing the use of a pre-calculated auto-ignition table. Auto-ignition is tabulated through adiabatic constant pressure reactor calculations. The tabulated chemistry based implementation has been assessed against the previously presented DI-SRM version by Pasternak et al. where chemical reactions are solved online. The chemical mechanism used in this work for both, online chemistry run and table generation, is an extended version of the scheme presented by Nawdial et al. The main fuel species are n-decane, α-methylnaphthalene and methyl-decanoate giving a size of 463 species and 7600 reactions. A single-injection part-load heavy-duty Diesel engine case with 28 % EGR fueled with regular Diesel is investigated with both tabulated and online chemistry. Comparisons between the two approaches are presented by means of overall engine performance and engine-out emission predictions and in equivalence ratio-temperature space. The new implementation delivers reasonably good agreement with the online chemistry one. The methodology presented in this paper allows for the use of detailed chemistry in the DI-SRM with high computational efficiency and thus facilitates the use of the DI-SRM in the engine development process. Copyright © 2017 SAE International.


Aslanjan J.,TU Brandenburg | Klauer C.,LOGE AB | Perlman C.,LOGE AB | Gunther V.,LOGE AB | Mauss F.,TU Brandenburg
SAE Technical Papers | Year: 2017

The three-way catalytic converter (TWC) is the most common catalyst for gasoline engine exhaust gas after treatment. The reduction of carbon monoxide (CO), nitrogen oxides (NOx) and unburned hydrocarbons (HC) is achieved via oxidation of carbon monoxide and hydrocarbons, and reduction of nitrogen oxides. These conversion effects were simulated in previous works using single-channel approaches and detailed kinetic models. In addition to the single-channel model multiple representative catalyst channels are used in this work to take heat transfer between the channels into account. Furthermore, inlet temperature distribution is considered. Each channel is split into a user given number of cells and each cell is treated like a perfectly stirred reactor (PSR). The simulation is validated against an experimental four-stroke engine setup with emission outputs fed into a TWC. Next to the transient emissions the temperature progress is simulated in order to model the catalyst's light off temperature. The heat conduction between the channels is modeled to provide proper heat dissipation during the catalytic process. The simulation results show a good agreement to the experimental data with low computational cost. Copyright © 2017 SAE International.


Mauss F.,TU Brandenburg | Ebenezer N.,TU Brandenburg | Lehtiniemi H.,LOGE AB
SAE Technical Papers | Year: 2010

The solution mapping method Adaptive Polynomial Tabulation (APT) for complex chemistry is presented. The method has the potential of reducing the computational time required for stochastic reactor model simulations of the HCCI combustion process. In this method the solution of the initial value chemical rate equation system is approximated in real-time with zero, first and second order polynomial expressions. These polynomials are algebraic functions of a progress variable, pressure and total enthalpy. The chemical composition space is divided a priori into block-shaped regions (hypercubes) of the same size. Each hypercube may be divided in real-time into adaptive hypercubes of different sizes. During computations, initial conditions are stored in the adaptive hypercubes. Two concentric Ellipsoids of Accuracy (EOA) are drawn around each stored initial condition. The time evolution of additional initial conditions which enter the inner EOA and outer EOA are approximated by zero and first order polynomials respectively. With a certain number of stored initial conditions in the adaptive hypercube, the second order polynomial coefficients are constructed from stored initial condition information. When an initial condition enters this adaptive hypercube, its ODE solution is calculated by evaluating the second order polynomials. The APT model is tested with a zero dimensional Stochastic Reactor Model (SRM) for HCCI engine combustion. A skeletal n-heptane/toluene mechanism with 137 chemical species and 1302 reactions is used. In the tests, the HCCI engine simulations using APT are in very good agreement with the model calculations using the ODE solver. The cool flame and main ignition events are accurately captured. The computational performance of the SRM-HCCI engine model is improved by a factor of 12. Copyright © 2010 SAE International.

Loading LOGE AB collaborators
Loading LOGE AB collaborators