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The regulations for mobile applications will become stricter in Euro 6 and further emission levels and require the use of active aftertreatment methods for NOX and particulate matter. SCR and LNT have been both used commercially for mobile NOX removal. An alternative system is based on the combination of these two technologies. Developments of catalysts and whole systems as well as final vehicle demonstrations are discussed in this study. The small and full-size catalyst development experiments resulted in PtRh/LNT with optimized noble metal loadings and Cu-SCR catalyst having a high durability and ammonia adsorption capacity. For this study, an aftertreatment system consisting of LNT plus exhaust bypass, passive SCR and engine independent reductant supply by on-board exhaust fuel reforming was developed and investigated. The concept definition considers NOX conversion, CO2 drawback and system complexity.

Multiple-injection strategies are widely used in DI diesel engines. However, the interaction of the injection pulses is not yet fully understood. In this work, a split injection into a combustion vessel is studied by multiple optical imaging diagnostics. The vessel provides quiescent high-temperature, high-pressure ambient conditions. A common-rail injector which is equipped with a three-hole nozzle is used. The spray is visualized by Mie scattering. First and second stage of ignition are probed by formaldehyde laser-induced fluorescence (LIF) and OH* chemiluminescence imaging, respectively. In addition formation of soot is characterized by both laser-induced incandescence (LII) and natural luminosity imaging, showing that low-sooting conditions are established. These qualitative diagnostics yield ensemble-averaged, two-dimensional, time-resolved distributions of the corresponding quantities.

With Post Euro 6 emission standards in discussion, stricter particulate number (PN) targets as well as a decreased PN cut-off size from 23 to 10 nm are expected. Sub-23 nm particulates are considered particularly harmful to human health, but are not yet taken into account in the current vehicle certification process. Not considering sub-23 nm particulates during the development process could lead to significant additional efforts for Original Equipment Manufacturers (OEM) to comply with future Post Euro 6 PN emission limits. It is therefore essential to increase knowledge about the formation and filtration of particulates below 23 nm. In the present study, a holistic Gasoline Particulate Filter (GPF) characterization has been carried out on an engine test bench under varying boundary conditions and on a burner bench with a novel ash loading methodology.

A new approach is presented to modelling wall heat transfer in the exhaust port and manifold within 1D gas exchange simulation to ensure a precise calculation of thermal exhaust enthalpy. One of the principal characteristics of this approach is the partition of the exhaust process in a blow-down and a push-out phase. In addition to the split in two phases, the exhaust system is divided into several sections to consider changes in heat transfer characteristics downstream the exhaust valves. Principally, the convective heat transfer is described by the characteristic numbers of Nusselt, Reynolds and Prandtl. However, the phase individual correlation coefficients are derived from 3D CFD investigations of the flow in the exhaust system combined with Low-Re turbulence modelling. Furthermore, heat losses on the valve and the seat ring surfaces are considered by an empirical model approach.

The interaction of biofuel sprays from an outward opening hollow cone injector and the flow field inside an internal combustion engine is analyzed by Mie-Scattering Imaging (MSI) and high-speed stereoscopic particle-image velocimetry (stereo-PIV). Two fuels (ethanol and methyl ethyl ketone (MEK)), four injection pressures (50, 100, 150, and 200 bar), three starting points of injection (60°, 277°, and 297° atdc), and two engine speeds (1,500 rpm and 2,000 rpm) define the parameter space of the experiments. The MSI measurements determine the vertical penetration length and the spray cone angle of the ethanol and MEK spray. Stereo-PIV is used to investigate the interaction of the flow field and the ethanol spray after the injection process for a start of injection at 60° atdc. These measurements are compared to stereo-PIV measurements without fuel injection performed in the same engine [19].

The influence of two oxygenated tailor-made fuels on soot formation and oxidation in an optical single cylinder research diesel engine has been studied. For the investigation a planar laser-induced incandescence (PLII) measurement technique was applied to the engine in order to detect and evaluate the planar soot distribution for the two bio fuels within a laser light sheet. Furthermore the OH* chemiluminescence and broad band soot luminosity was visualized by high speed imaging to compare the ignition and combustion behavior of tested fuels: Two C8 oxygenates, di-n-butylether (DNBE) and 1-octanol. Both fuels have the same molecular formula but differ in their molecular structure. DNBE ignites fast and burns mostly diffusive while 1-octanol has a low cetane number and therefore it has a longer ignition delay but a more homogeneous mixture at time of ignition. The two bio fuels were finally compared to conventional diesel fuel.

Stochastic Pre-Ignition (SPI) or Low Speed Pre-Ignition (LSPI) is an abnormal combustion event that can occur during the operation of modern, highly boosted direct-injection gasoline engines. This abnormal combustion event is characterized by an undesired and early start of combustion that is not initiated by the spark plug. Early SPI events can subsequently lead to violent auto-ignitions that are referred to as Mega- or Super-Knock in literature and have the potential to severely damage engines in the field. Numerous studies to analyze impact factors on SPI occurrence and severity have been conducted in recent years. While initial studies have focused strongly on engine oil formulation, calibration and engine design and their respective impact on SPI initiation, the impact of physical and chemical properties of the fuel have also become of interest in recent years.

The technological advancements of Advanced Driver Assistance Systems (ADAS) sensors enable the ability to; achieve autonomous vehicle platooning, increase the capacity of road lanes, and reduce traffic. This article focuses on developing urban autonomous platooning using LiDAR and GPS/IMU sensors in a simulation environment. Gazebo simulation is utilized to simulate the sensors, vehicles, and testing environment. Two vehicles are used in this study; a Lead vehicle that follows a preplanned trajectory, while the remaining vehicle (Follower) uses the LiDAR object detection and tracking information to mimic the Lead vehicle. The LiDAR object detection is handled in multiple stages: point cloud frame transformation, filtering and down-sampling, ground segmentation, and clustering. The tracking algorithm uses the clustering information to provide position and velocity of the Lead vehicle which allows for vehicle platooning.

Past experimental studies conducted by the current authors on a 13 liter 16.7:1 compression ratio heavy-duty diesel engine have shown that diesel-Compressed Natural Gas (CNG) Reactivity Controlled Compression Ignition (RCCI) combustion targeting low NOx emissions becomes progressively difficult to control as the engine load is increased. This is mainly due to difficulty in controlling reactivity levels at higher loads. For the current study, CFD investigations were conducted in CONVERGE using the SAGE combustion solver with the application of the Rahimi mechanism. Studies were conducted at a load of 5 bar BMEP to validate the simulation results against RCCI experimental data. In the low load study, it was found that the Rahimi mechanism was not able to predict the RCCI combustion behavior for diesel injection timings advanced beyond 30 degCA bTDC. This poor prediction was found at multiple engine speed and load points.

On the way to emission-free mobility, future fuels must be CO2 neutral. To achieve this, synthetic fuels are being developed. In order to better assess the effects of the new fuels on the engine process, simulation models are being developed that reproduce the chemical and physical properties of these fuels. In this paper, the fuel DMC+ is examined. DMC+ (a mixture of dimethyl carbonate (DMC) and methyl formate (MeFo) mainly, characterized by the lack of C-C Bonds and high oxygen content) offers advantages with regard to evaporation heat, demand of oxygen and knock resistance. Furthermore, its combustion is almost particle free. With the aid of modern 0D/1D simulation methods, an assessment of the potential of DMC+ can be made. It is shown that the simulative conversion of a state-of-the-art gasoline engine to DMC+ fuel offers advantages in terms of efficiency in many operating points even if the engine design is not altered.

Due to increasing environmental awareness, standards for pollutant and CO2 emissions are getting stricter in most markets around the world. In important markets such as Europe, also the emissions during real road driving, so called “Real Driving Emissions” (RDE), are now part of the type approval process for passenger cars. In addition to the proceeding hybridization and electrification of vehicles, the complexity and degrees of freedom of conventional powertrains with internal combustion engines (ICE) are also continuing to increase in order to comply with stricter exhaust emission standards. Besides the different requirements placed on vehicle emissions, the drivability capabilities of passenger vehicles desired by customers, are essentially important and vary between markets.

Advanced Driver Assistance Systems (ADAS) enable safer driving by relying on the inputs from various sensors including Radar, Camera, and LiDAR. One of the newly emerging ADAS features is Predictive Cruise Control (PCC). PCC aims to optimize the vehicle’s speed profile and fuel efficiency. This paper presents a novel approach of using the point cloud of a LiDAR sensor to develop a PCC feature. The raw point cloud is utilized to detect objects in the surrounding environment of the vehicle, estimate the grade of the road, and plan the route in drivable areas. This information is critical for the PCC to define the optimal speed profile of the vehicle while following the planned path. This paper also discusses the developed algorithms of the LiDAR data processing and PCC controller. These algorithms were tested on FEV’s Smart Vehicle Demonstrator platform.

Direct injection (DI) of compressed natural gas (CNG) is a promising technology to increase the indicated thermal efficiency of internal combustion engines (ICE) while reducing exhaust emissions and using a relatively low-cost fuel. However, design and analysis of DI-CNG engines are challenging because supersonic gas jet emerging from the DI injector results in a very complex in-cylinder flow field containing shocks and discontinuities affecting the fuel-air mixing. In this article, numerical simulations are used supported by validation to investigate the direct gas injection and its influence on the flow field and mixing in an optically accessible ICE. The simulation approach involves computation of the in-nozzle flow with highly accurate Large-Eddy Simulations, which are then used to obtain a mapped boundary condition. The boundary condition is applied in Unsteady Reynolds Averaged Navier-Stokes simulations of the engine to investigate the in-cylinder velocity and mixing fields.

Within the Cluster of Excellence “Tailor-Made Fuels from Biomass” (TMFB) at the RWTH Aachen University, two novel biogenic fuels, namely 1-octanol and its isomer dibutyl ether (DBE), were identified and extensively analyzed in respect of their suitability for combustion in a Diesel engine. Both biofuels feature very different properties, especially regarding their ignitability. In previous works of the research cluster, promising synthesis routes with excellent yields for both fuels were found, using lignocellulosic biomass as source material. Both fuels were investigated as pure components in optical and thermodynamic single cylinder engines (SCE). For 1-octanol at lower part load, almost no soot emission could be measured, while with DBE the soot emissions were only about a quarter of that with conventional Diesel fuel. At high part load (2400 min-1, 14.8 bar IMEP), the soot reduction of 1-octanol was more than 50% and for DBE more than 80 % respectively.

The performance of Gasoline Direct Injection (GDI) engines is governed by multiple physical processes such as the internal nozzle flow and the mixing of the liquid stream with the gaseous ambient environment. A detailed knowledge of these processes even for complex injectors is very important for improving the design and performance of combustion engines all the way to pollutant formation and emissions. However, many processes are still not completely understood, which is partly caused by their restricted experimental accessibility. Thus, high-fidelity simulations can be helpful to obtain further understanding of GDI injectors. In this work, advanced simulation and experimental methods are combined in order to study the spray characteristics of two different 3-hole GDI injectors.

In order to thoroughly investigate and improve the path from biofuel production to combustion, the Cluster of Excellence “Tailor-Made Fuels from Biomass” was installed at RWTH Aachen University in 2007. Since then, a variety of fuel candidates have been investigated. In particular, 2-methyl tetrahydrofurane (2-MTHF) has shown excellent performance w.r.t. the particulate (PM) / NOx trade-off [1]. Unfortunately, the long ignition delay results in increased HC-, CO- and noise emissions. To overcome this problem, the addition of di-n-butylether (DNBE, CN ∼ 100) to 2-MTHF was analyzed. By blending these two in different volumetric shares, the effects of the different mixture formation and combustion characteristics, especially on the HC-, CO- and noise emissions, have been carefully analyzed. In addition, the overall emission performance has been compared to EN590 diesel.

Autonomous driving in unstructured environments is a significant challenge due to the inconsistency of important information for localization such as lane markings. To reduce the uncertainty of vehicle localization in such environments, sensor fusion of LiDAR, Radar, Camera, GPS/IMU, and Odometry sensors is utilized. This paper discusses a hybrid localization technique developed using: LiDAR-based Simultaneous Localization and Mapping (SLAM), GPS/IMU, Odometry data, and object lists from Radar, LiDAR, and Camera sensors. An Extended Kalman Filter (EKF) is utilized to fuse data from all sensors in two phases. In the preliminary stage, the SLAM-based vehicle coordinates are fused with the GPS-based positioning. The output of this stage is then fused with the object-based localization. This approach was successfully tested on FEV’s Smart Vehicle Demonstrator at FEV’s HQ. It represented a complicated test environment with dynamic and static objects.

In Common-Rail DI Diesel Engines, a low combustion temperature process is considered as one of the most important possibilities to achieve very small emissions and optimum performance. To reduce NOx and Soot strongly, it is necessary to achieve a homogenization of the mixture in order to avoid the higher local temperatures which are responsible for the NOx formation [1]. Through the homogenization it is also possible to obtain a stoichiometric air-fuel ratio in order to significantly reduce the Soot emissions. One way to achieve this homogeneous condition is to start injection very early together with the use of higher EGR rates. The direct effect of these conditions cause a longer ignition delay (this is the time between start of the injection and auto-ignition during physical and chemical sub processes such as fuel atomization, evaporation, fuel air mixing and chemical pre-reactions take place) so that the mixture formation has more time to achieve a homogeneous state.

One of the basic topics in the design of new injection systems for DI Diesel engines is to decrease the soot emissions. A promising approach to minimize soot production are nozzles with clustered holes. A basic idea of the Cluster Configuration (CC) nozzles is to prevent a fuel rich area in the center of the flame where most of the soot is produced, and to minimize the overall soot formation in this way. For this purpose each hole of a standard nozzle is replaced by two smaller holes. The diameter of the smaller holes is chosen so that the flow rate of all nozzles should be equal. The basic strategy of the cluster nozzles is to provide a better primary break up and therefore a better mixture formation caused by the smaller nozzle holes, but a comparable penetration length of the vapor phase due to merging of the sprays. Three possible arrangements of the clustered holes are investigated in this study. Both the cluster angle and the orientation to the injector axis are varied.

Recently, fuels containing ethanol have become more and more important for spark ignition engines. Fuels with up to 10 vol.-% ethanol can be used in most spark ignition engines without technical modification. These fuels have been introduced in many countries already. Alternatively, for fuels with higher amounts of ethanol so called flex fuel vehicles (FFV) exist. One of the most important quantities characterizing a fuel is the laminar burning velocity. To account for the new fuels with respect to engine design, reliable data need to be existent. Especially for engine simulations, various combustion models have been introduced which rely on the laminar burning velocity as the physical quantity describing the progress of chemical reactions, diffusion, and heat conduction. However, there is very few data available in the literature for fuels containing ethanol, especially at high pressures.