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- (CPV) Approach for Engine Applications (1)
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- Development of a Computationally Efficient Progress (1)
- Diesel Engine, Stochastic Reactor Modeling, Particlulate Matter (1)
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BTU
Highly fuel-efficient Diesel engines, combined with effective exhaust aftertreatment systems, enable an economic and low-emission operation of heavy-duty vehicles. The challenge of its development arises from the present engine complexity, which is expected to increase even more in the future. The approved method of test bench measurements is stretched to its limits, because of the high demand for large parameter variations. The introduction of a physics-based quasi-dimensional stochastic reactor model combined with tabulated chemistry enables the simulation-supported development of these Diesel 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 …
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.
A Computationally Efficient Combustion Progress Variable (CPV) Approach for Engine Applications
(2018)
Advanced Predictive Diesel Combustion Simulation Using Turbulence Model and Stochastic Reactor Model
(2017)
Several models for ignition, combustion and emission formation under diesel engine conditions for multi-dimensional computational fluid dynamics have been proposed in the past. It has been recognized that the use of a reasonably detailed chemistry model improves the combustion and emission prediction especially under low temperature and high exhaust gas recirculation conditions.The coupling of the combustion chemistry and the turbulent flow can be achieved with different assumptions. In this paper we investigate a selection of n-heptane spray experiments published by the Engine Combustion Network (ECN spray H) with three different combustion models: well-stirred reactor model, transient interactive flamelet model and progress variable based conditional moment closure. All models cater for the use of detailed chemistry, while the turbulence-chemistry interaction modeling and the ability to consider local effects differ.The same chemical mechanism is used by all combustion models, which allows a comparison of ignition delay, flame stabilization and flame lift-off length between the experiments and the results from simulations using the different combustion models. The investigated parameters influence the predictions of computational fluid dynamics simulations of diesel engines. This study indicates that the most reasonable behavior with respect to ignition, flame stabilization and flame structure is predicted by the progress variable based conditional moment closure model.