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Technical Paper

Multi-Objective Optimization of Fuel Consumption and NOx Emissions with Reliability Analysis Using a Stochastic Reactor Model

2019-04-02
2019-01-1173
The introduction of a physics-based zero-dimensional stochastic reactor model combined with tabulated chemistry enables the simulation-supported development of future compression-ignited engines. The stochastic reactor model mimics mixture and temperature inhomogeneities induced by turbulence, direct injection and heat transfer. Thus, it is possible to improve the prediction of NOx emissions compared to common mean-value models. To reduce the number of designs to be evaluated during the simulation-based multi-objective optimization, genetic algorithms are proven to be an effective tool. Based on an initial set of designs, the algorithm aims to evolve the designs to find the best parameters for the given constraints and objectives. The extension by response surface models improves the prediction of the best possible Pareto Front, while the time of optimization is kept low.
Journal Article

Numerical Analysis of the Impact of Water Injection on Combustion and Thermodynamics in a Gasoline Engine Using Detailed Chemistry

2018-04-03
2018-01-0200
Water injection is a promising technology to improve the fuel efficiency of turbocharged gasoline engines due to the possibility to suppress engine knock. Additionally, this technology is believed to enable the efficient operation of the three-way catalyst also at high-load conditions, through limiting the exhaust temperature. In this numerical study, we investigate the effect of water on the chemical and thermodynamic processes using 3D computational fluid dynamics (CFD) Reynolds-averaged Navier–Stokes (RANS) with detailed chemistry. In the first step, the influence of different amounts of water vapor on ignition delay time, laminar flame speed, and heat capacity is investigated. In the second step, the impact of water vaporization is analyzed for port and direct injection. For this purpose, the water mass flow and the injection pressure are varied.
Technical Paper

Advanced Predictive Diesel Combustion Simulation Using Turbulence Model and Stochastic Reactor Model

2017-03-28
2017-01-0516
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.
Technical Paper

Development of a Computationally Efficient Progress Variable Approach for a Direct Injection Stochastic Reactor Model

2017-03-28
2017-01-0512
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.
Technical Paper

Development of Methodology for Predictive Diesel Combustion Simulation Using 0D Stochastic Reactor Model

2016-04-05
2016-01-0566
Stringent exhaust emission limits and new vehicle test cycles require sophisticated operating strategies for future diesel engines. Therefore, a methodology for predictive combustion simulation, focused on multiple injection operating points is proposed in this paper. The model is designated for engine performance map simulations, to improve prediction of NOx, CO and HC emissions. The combustion process is calculated using a zero dimensional direct injection stochastic reactor model based on a probability density function approach. Further, the formation of exhaust emissions is described using a detailed reaction mechanism for n-heptane, which involves 56 Species and 206 reactions. The model includes the interaction between turbulence and chemistry effects by using a variable mixing time profile. Thus, one is able to capture the effects of mixture inhomogeneities on NOx, CO and HC emission formation.
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