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%).

Lean-Blow-Out Simulation of Natural Gas Fueled, Premixed Turbulent Jet Flame Arrays With LES and FGM-Modeling

To ensure compliance with stricter regulations on exhaust gas emissions, new industrial burner concepts are being investigated. One of these concepts is the matrix burner, consisting of an array of premixed, non-swirling jet flames. For the design of such burners, the prediction of fundamental burner properties is mandatory. One of these essential quantities is the lean blowout limit (LBO), which has already been investigated experimentally. This study investigates the possibility of numerical LBO prediction using a tabulated chemistry approach in combination with Large-Eddy-Simulation turbulence modeling. In contrast to conventional swirl burners, the numerical description of blowout events of multi jet flames has not yet been studied in detail. Lean blowout simulations have therefore been conducted for multiple nozzle variants, varying in their diameter and global dump ratio for a variety of operating conditions, showing their general applicability. A procedure to induce LBO is introduced where a stepwise increase in total mass flow is applied. LBO is determined based on the temporal progress of the mean reaction rate. A comparison with measurements shows good agreement and demonstrates that the procedure developed here is an efficient way to predict LBO values. Further investigations focused on the flame behavior when approaching LBO. The flame shape shows a drastic change from single jet flames (stable conditions) to a joint conical flame approaching LBO, which increases in length for increasing inlet velocity, showing the importance of jet interaction at LBO.

Computational Modeling of Boundary Layer Flashback in a Swirling Stratified Flame Using a LES-Based Non-Adiabatic Tabulated Chemistry Approach

When operating under lean fuel–air conditions, flame flashback is an operational safety issue in stationary gas turbines. In particular, with the increased use of hydrogen, the propagation of the flame through the boundary layers into the mixing section becomes feasible. Typically, these mixing regions are not designed to hold a high-temperature flame and can lead to catastrophic failure of the gas turbine. Flame flashback along the boundary layers is a competition between chemical reactions in a turbulent flow, where fuel and air are incompletely mixed, and heat loss to the wall that promotes flame quenching. The focus of this work is to develop a comprehensive simulation approach to model boundary layer flashback, accounting for fuel–air stratification and wall heat loss. A large eddy simulation (LES) based framework is used, along with a tabulation-based combustion model. Different approaches to tabulation and the effect of wall heat loss are studied. An experimental flashback configuration is used to understand the predictive accuracy of the models. It is shown that diffusion-flame-based tabulation methods are better suited due to the flashback occurring in relatively low-strain and lean fuel–air mixtures. Further, the flashback is promoted by the formation of features such as flame tongues, which induce negative velocity separated boundary layer flow that promotes upstream flame motion. The wall heat loss alters the strength of these separated flows, which in turn affects the flashback propensity. Comparisons with experimental data for both non-reacting cases that quantify fuel–air mixing and reacting flashback cases are used to demonstrate predictive accuracy.

Non-Premixed Filtered Tabulated Chemistry: Filtered Flame Modeling of Diffusion Flames

The flame front filtering is a well-known strategy in turbulent premixed combustion. An extension of this approach for the non-premixed combustion context has been proposed by means of directly filtering counterflow diffusion flamelets. Promising results were obtained for the non-premixed filtered tabulated chemistry formalism on 1-D and 2-D unresolved counterflow flame configurations. The present paper demonstrates the soundness of this approach on a 3-D real laminar non-premixed coflow flame. The model results are compared against the direct filtering of the fully resolved laminar diffusion flame showing that the formalism adequately describes the underlying physics. The study reveals the importance of the one-dimensional counterflow flamelet hypothesis, so that the model activation under this condition is ensured by means of a flame sensor. The consistent coupling between the model and the flame sensor adequately retrieves the flame lift-off and satisfactorily predicts the profile extension due to the filtering process.