Real-Time Emission Prediction with Detailed Chemistry under Transient Conditions for Hardware-in-the-Loop Simulations

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%).

An approach to the assessment of dimethyl carbonate and ethanol effect as gasoline oxygenating agents under engine conditions via a Computational Fluid Dynamics model

An ASTM-CFR engine was modeled through Computational Fluid Dynamics (CFD) coupled with chemical kinetics to evaluate the effect on combustion characteristics and engine emissions of dimethyl carbonate (DMC) and ethanol as gasoline components, the latter as reference oxygenating agent. Validation against experimental in-cylinder pressure data indicated adequate reproduction of these fuels combustion, all blends showing higher and earlier pressure peaks than neat gasoline (ca. 0.2 MPa and 2 CAD). Simulated temperatures were close for all fuels, though slightly advanced for the oxygenated blends (ca. 2 CAD). Similar behavior of the oxygenates was predicted regarding HC, CO and soot emissions: ca. 90% reduction in HC, CO, and soot emissions were observed, but ethanol displayed up to 3.5% CO2 reduction and 17% NOx increase, while DMC showed up to 7% decrease in CO2 and 6% increase in NOx. Considering the advantage of using chemical kinetics for combustion calculations in the CFD model, i.e., quantification of any species present in the reaction mechanism, including those difficult to observe/measure experimentally, concentrations of non-regulated emissions (e.g., formaldehyde) were studied. In particular, a minor increase in formaldehyde emissions was found with both oxygenated fuels. Albeit a first approach to assessing oxygenating compounds effects on gasoline combustion and emissions under engine conditions through a CFD + detailed chemistry model, the results underline the potential of DMC as gasoline oxygenating agent, and are a starting point for studying non-measured/non-regulated species and parametric engine analysis in future models.

CFD Modeling of Low Temperature Ignition Processes From a Nanosecond Pulsed Discharge at Quiescent Conditions

Recent interest in non-equilibrium plasma discharges as sources of ignition for the automotive industry has not yet been accompanied by the availability of dedicated models to perform this task in computational fluid dynamics (CFD) engine simulations. The need for a low-temperature plasma (LTP) ignition model has motivated much work in simulating these discharges from first principles. Most ignition models assume that an equilibrium plasma comprises the bulk of discharge kernels. LTP discharges, however, exhibit highly non-equilibrium behavior. In this work, a method to determine a consistent initialization of LTP discharge kernels for use in engine CFD codes like CONVERGE is proposed. The method utilizes first principles discharge simulations. Such an LTP kernel is introduced in a flammable mixture of air and fuel, and the subsequent plasma expansion and ignition simulation is carried out using a reacting flow solver with detailed chemistry. The proposed numerical approach is shown to produce results that agree with experimental observations regarding the ignitability of methane-air and ethylene-air mixtures by LTP discharges.

Analysis of Local Exergy Losses in Combustion Systems Using a Hybrid Filtered Eulerian Stochastic Field Coupled with Detailed Chemistry Tabulation: Cases of Flames D and E

A second law analysis in combustion systems is performed along with an exergy loss study by quantifying the entropy generation sources using, for the first time, three different approaches: a classical-thermodynamics-based approach, a novel turbulence-based method and a look-up-table-based approach, respectively. The numerical computation is based on a hybrid filtered Eulerian stochastic field (ESF) method coupled with tabulated detailed chemistry according to a Famelet-Generated Manifold (FGM)-based combustion model. In this work, the capability of the three approaches to capture the effect of the Re number on local exergy losses is especially appraised. For this purpose, Sandia flames D and E are selected as application cases. First, the validation of the computed flow and scalar fields is achieved by comparison to available experimental data. For both flames, the flow field results for eight stochastic fields and the associated scalar fields show an excellent agreement. The ESF method reproduces all major features of the flames at a lower numerical cost. Next, the second law analysis carried out with the different approaches for the entropy generation computation provides comparable quantitative results. Using flame D as a reference, for which some results with the thermodynamic-based approach exist in the literature, it turns out that, among the sources of exergy loss, the heat transfer and the chemical reaction emerge notably as the main culprits for entropy production, causing 50% and 35% of it, respectively. This fact-finding increases in Sandia flame E, which features a high Re number compared to Sandia flame D. The computational cost is less once the entropy generation analysis is carried out by using the Large Eddy Simulation (LES) hybrid ESF/FGM approach together with the look-up-table-based or turbulence-based approach.

Applying detailed chemistry for the dual-fuel engine combustion process simulation using CFD approach

Modern research in the area of internal combustion engines is focused on searching and investigating the technologies that will improve fuel efficiency and decrease emissions. The application of dual-fuel engines is considered a potential solution to these problems. In the dual-fuel engine, the natural gas-air mixture is ignited by a small amount of diesel fuel directly injected into a combustion chamber. This paper aims to develop a detailed chemistry mechanism for 3D simulation of the combustion process of a dual-fuel engine, providing sufficient convergence with the experimental data. It should be noted that sufficient convergence must also be provided in terms of such parameters as pilot fuel ignition delay and premixed air-fuel mixture flame propagation speed. In the course of the research, the analysis of the most commonly used detailed chemistry mechanisms for calculation of the combustion process and mechanisms’ disadvantages was performed. The results obtained with the use of the detailed mechanisms were compared with the results obtained without using detailed chemistry and with the experimental data as well.

The challenges of using detailed chemistry model for simulating direct injection spark ignition engine combustion during cold-start

Computational Fluid Dynamics (CFD) modeling of gasoline spark-ignited engine combustion has been extensively discussed using both detailed chemistry mechanisms (e.g., SAGE) and flamelet models (e.g., the G-equation). The models have been extensively validated under normal operating conditions; however, few studies have discussed the capability of these models in capturing DISI combustion under cold-start conditions. A cold-start differs from normal operating conditions in various respects, such as (1) having highly retarded spark timing to help generate a high heat flux in the exhaust for a rapid catalyst light-off; (2) having split-injection strategies to ensure a favorable stratification at the vicinity of the spark plug and reduced film formation; and (3) having optimized valve timings for reduced NOx emissions via increased internal residuals and reduced hydrocarbon (HC) emissions via prolonged oxidation of the combustion products. The retarded spark timing introduces the adverse effect of a decaying turbulence field, which results in a reduced turbulent flame speed. The analysis of all these factors happening inside the cylinder appears complicated at first glance; however, it could be made possible by efficient use of the existing CFD models. The current study explored the capability of the SAGE detailed chemistry model in capturing cold-start flame travel in a DISI engine. The results were then compared against the G-equation-based GLR model, which has been validated for excellent predictions of the DISI cold-start combustion as shown by Ravindran et al. The flame travel was captured on a Borghi-Peters diagram to find that the flame travels through corrugated, wrinkled, and laminar regimes. In order to fully evaluate the capability of the detailed chemistry model in predicting such changing turbulence-chemistry interactions, it will need to be studied individually in each regime; however, the scope of the current paper is limited to the study of the model behavior in the laminar regime, which will be shown to be important for DISI engine cold-start. The SAGE detailed chemistry model, with a toluene reference fuel (TRF) mechanism validated for gasoline laminar flame speeds, was found to significantly under-predict the flame propagation speeds because of the effects of numerical viscosity and discrepancies in capturing molecular diffusion. The causes and effects of this under-prediction and the ways in which this can be improved are presented in the paper.