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In order to improve the efficiency of passenger cars, developments focus on decreasing their aerodynamic drag, part of which is caused by cooling air. Thus, car manufacturers try to seal the cooling air path to prevent leakage flows. Nevertheless, gaps between the single components of the cooling air path widen due to the deformation of components under aerodynamic load. For simulating the cooling airflow utilization ratio (CAUR), computational fluid dynamics (CFD) simulations are used, which neglect component deformation. In this paper, a computational method aiming at sufficient gap resolution and determining the CAUR of passenger cars under the consideration of component deformation is developed. Therefore, a partitioned approach of fluid structure interaction (FSI) simulations is used. The fluid field is simulated in OpenFOAM, whereas the structural simulations are conducted using Pam-Crash.

EU legislation provides for only local CO2 emission-free vehicles to be allowed in individual passenger transport by 2035. In addition, the directive provides for fuels from renewable sources, i.e. defossilised fuels. This development leads to three possible energy sources or forms of energy for use in individual transport. The first possibility is charging with electricity generated from renewable sources, the second possibility is hydrogen generated from renewable sources or blue production path. The third possibility is the use of renewable fuels, also called e-fuels. These fuels are produced from atmospheric CO2 and renewable hydrogen. Possible processes for this are, for example, methanol or Fischer-Tropsch synthesis. The production of these fuels is very energy-intensive and large amounts of renewable electricity are needed.

The target of the upcoming automotive emission regulations is to promote a fast transition to near-zero emission vehicles. As such, the range of ambient and operating conditions tested in the homologation cycles is broadening. In this context, the proposed work aims to thoroughly investigate the potential of post-oxidation phenomena in reducing the light-off time of a conventional three-way catalyst. The study is carried out on a turbocharged four-cylinder gasoline engine by means of experimental and numerical activities. Post oxidation is achieved through the oxidation of unburned fuel in the exhaust line, exploiting a rich combustion and a secondary air injection dedicated strategy. The CFD methodology consists of two different approaches: the former relies on a full-engine mesh, the latter on a detailed analysis of the chemical reactions occurring in the exhaust line.

Dust testing of vehicles on unpaved roads is crucial in the development process for automotive manufacturers. These tests aim to ensure the functionality of locking systems in dusty conditions, minimize dust concentration inside the vehicle, and enhance customer comfort by preventing dust accumulation on the car body. Additionally, deposition on safety-critical parts, such as windshields and sensors, can pose threats to driver vision and autonomous driving capabilities. Currently, dust tests are primarily conducted experimentally at proving grounds. In order to gain early insights and reduce the need for costly physical tests, numerical simulations are becoming a promising alternative. Although simulations of vehicle contamination by dry dust have been studied in the past, they have often lacked detailed models for tire dust resuspension. In addition, few publications address the specifics of dust deposition on vehicles, especially in areas such as door gaps and locks.

The improvement of vehicle soiling behavior has increasing interest over the past few years not only to satisfy customer requirements and ensure a good visibility of the surrounding traffic but also for autonomous vehicles, for which soiling investigation and improvement are even more important due to the demands of the cleanliness and induced functionality of the corresponding sensors. The main task is the improvement of the soiling behavior, i.e., reduction or even prevention of soiling of specific surfaces, for example, windows, mirrors, and sensors. This is mostly done in late stages of vehicle development and performed by experiments, e.g., wind tunnel tests, which are supplemented by simulation at an early development stage. Among other sources, the foreign soiling on the side mirror and the side window depend on the droplet detaching from the side mirror housing.

In order to achieve the climate targets, a mix of different powertrain technologies must be pursued to effectively reduce emissions. By producing hydrogen based on renewable energy sources, it becomes a reasonable choice for fueling internal combustion engines. The specific molecular properties of hydrogen thereby open up new possibilities for favorably influencing the combustion process of engines. The present paper deals with the analysis of a single-cylinder engine with passive pre-chamber ignition and a port fuel injection system, which was adapted for lean hydrogen operation. In this way, the test unit was operated in various load and speed ranges with lambda values from 1.5 to 2.5 and achieved up to 23 bar indicated mean effective pressure. The focus of this work is on the numerical investigation of the hydrogen combustion and its effects on the engine system. Special attention is hereby paid to the influence of different lambda operations.

There is a growing need for low-emissions concepts due to stricter emission regulations, more stringent homologation cycles, and the possibility of a ban on new engines by 2035. Of particular concern are the conditions during a cold start, when the Three-Way Catalyst is not yet heated to its light-off temperature. During this period, the catalyst remains inactive, thereby failing to convert pollutants. Reducing the time needed to reach this temperature is crucial to comply with the more stringent emissions standards. The post oxidation by means of secondary air injection, illustrated in this work, is a possible solution to reduce the time needed to reach the above-mentioned temperature. The strategy consists of injecting air into the exhaust manifold via secondary air injectors to oxidize unburned fuel that comes from a rich combustion within the cylinder.

Due to increasingly strict emission regulations, lean combustion concept has become an essential direction of internal combustion engine development to reduce engine emissions. However, lean combustion will lead high combustion instability and unpredictive engine emissions. The combustion instability is represented as the high cycle-to-cycle variation. Therefore, understanding the mechanism of cycle-to-cycle variation is crucial for the internal combustion engine design. This paper investigates the cause-and-effect chain of cycle-to-cycle variation of spark ignition engines using 3D CFD simulations with CONVERGE v3.0. The cyclic variations were simulated through Large Eddy Simulations, and the simulations based on Reynolds-averaged Navier–Stokes were used as supplements. The analysis focuses on two key factors that determine the combustion process: the turbulent intensity and the homogeneity of the air/fuel mixture.

The proportion of new registrations with battery-electric and hybrid powertrains is rising steadily. This shows the strong trend in the automotive industry away from conventional powertrains with internal combustion engines. The aim is to reduce the transport sector's contribution to CO2 emissions. However, it should be noted that this only applies when renewable energy is used. Studies show the relevance of the system boundaries under consideration, which makes the application of Life Cycle Assessment indispensable. According to these studies, the various types of powertrains differ only slightly in their greenhouse gas impact. Rather, the energy supply chain plays a significant role. Moreover, a ban on combustion engines would lead to an additional increase in cumulative CO2 emissions. An important aspect on the way to sustainable mobility solutions is addressing the existing fleet.

Whether as an optimization problem or a development tool, neural networks help engineers to work more efficiently. This paper’s central aspect is to add metadata to the core files of the project simulation data. To understand the project and its simulation models, a pre-processing methodology and convolutional neural network architecture are presented. With the added labels, it is possible to access the content of the model files of an engine performance simulation tool without examining them. At first, a pre-processing approach and its design are introduced to extract and filter the desired data from the XML data structure. Then, the data is split into sequences and paired with labels. Expert knowledge is used to label the models. These labels are further paired with the extracted sequences.

Numerical methodologies for aeroacoustic analyses are increasingly crucial for car manufacturers to optimize the effectiveness of vehicle development. In the present work, a hybrid numerical tool based on the combination of a delayed detached-eddy simulation and a finite element model, which relies on the Lighthill’s acoustic analogy and the acoustic perturbation equations, is presented. The computational aeroacoustics is performed by the software OpenFOAM and Actran, concerning respectively the CFD and the FEM. The aeroacoustic behavior of the SUV Lamborghini Urus at a cruising speed of 140 km/h has been investigated. The main aerodynamic noise phenomena occurring in the side mirror region in a frequency range up to 5 kHz are discussed. The numerical simulations have been verified against the measurements performed in the aeroacoustic wind tunnel of the University of Stuttgart, operated by FKFS.

Dry dust testing of vehicles on unpaved dust roads plays a crucial role in the development process of automotive manufacturers. One of the central aspects of the test procedure is ensuring the functionality of locking systems in the case of dust ingress and keeping the dust below a certain concentration level inside the vehicle. Another aspect is the customer comfort because of dust deposited on the surface of the car body. This also poses a safety risk to customers when the dust settles on safety-critical parts such as windshields and obstructs the driver’s view. Dust deposition on sensors is also safety critical and is becoming more important because of the increasing amount of sensors for autonomous driving. Nowadays, dust tests are conducted experimentally at dust proving grounds. To gain early insights and avoid costly physical testing, numerical simulations are considered a promising approach. Simulations of vehicle contamination by dry dust have been studied in the past.

A computational study of the vehicle aerodynamics influenced by the wake of the rotating wheel taking into account a detailed rim geometry is presently performed. The car configuration corresponds to a full-scale (1:1) notchback configuration of the well-known ‘DrivAer’ vehicle model, Heft et al. [1]. The objective of the present work is to investigate the performance of some popular turbulence models in conjunction with different methods for handling the wheel rotation – rotating wall velocity, ‘multiple reference frame’ and ‘sliding grid algorithm’. The specific focus hereby is on a near-wall RANS eddy-viscosity model based on elliptic-relaxation, sensitized to resolve fluctuating turbulence by introducing a specifically modeled production term in the scale-supplying equation, motivated by the Scale-Adaptive Simulation approach (SAS, [2]), proposed by Krumbein et al. [3].

Prospective combustion engine applications require the highest possible energy conversion efficiencies for environmental and economic sustainability. For conventional Spark-Ignition (SI) engines, the quasi-hemispherical flame propagation combustion method can only be significantly optimized in combination with high excess air dilution or increased combustion speed. However, with increasing excess air dilution, this is difficult due to decreasing flame speeds and flammability limits. Pre-Chamber (PC) initiated jet ignition combustion systems significantly shift the flammability and flame stability limits towards higher dilution areas due to high levels of introduced turbulence and a significantly increased flame area in early combustion stages, leading to considerably increased combustion speeds and high efficiencies. By now, vehicle implementations of PC-initiated combustion systems remain niche applications, especially in combination with lean mixtures.

The accelerated processes in vehicle development require new technologies for function development and validation. With this motivation, Function-in-the-Loop (FiL) simulation was developed as a link between Software-in-the-Loop (SiL) and Hardware-in-the-Loop (HiL) simulation. The combination of real Electronic Control Unit (ECU) hardware and software in conjunction with virtual components is very well suited for function development and testing. This approach opens up new possibilities for mechatronic systems that would otherwise require special test benches. For this reason, an Electric Power Steering (EPS) was transferred to a virtual environment using FiL simulation. This enables a wide range of applications, from EPS testing to the development of connected driving functions on an integrated platform. Right from the early development phases, the technology can be used purposefully with short integration cycles.

The investigation of vehicle soiling by improvement of vehicle parts to optimize the surrounding airflow is of great importance not only because of the visibility through windows and at mirrors but also the functionality of different types of sensors (camera, lidar, radars, etc.) for the driver assistance systems and especially for autonomous driving vehicles has to be guaranteed. These investigations and corresponding developments ideally take place in the early vehicle development process since later changes are difficult to apply in the vehicle production process for many reasons. Vehicle soiling is divided into foreign soiling and self-soiling with respect to the source of the soiling water, e.g., direct rain impact, swirled (dirty) water of other road users and own rotating wheels. The investigations of the soiling behavior of vehicles were performed experimentally in a wind tunnel and street tests.

Future combustion engine applications require highest possible energy conversion efficiencies to reduce their environmental impact and be economically competitive. So far, spark-ignition (SI) engine combustion development mostly consisted of optimizing the hemispherical flame propagation combustion method. Thereby, a significant efficiency increase is only achievable in combination with high excess air dilution or increased combustion speed. However, with increasing excess air dilution, this is difficult due to decreasing flame speeds and flammability limits. Simultaneously, researchers have been investigating homogeneous charge compression ignition (HCCI) that achieves higher efficiencies due to its rapid volume reaction combustion and also enables high excess air dilution. However, the combustion is complex to control as it is initiated by auto-ignition (AI) processes. In-cylinder conditions reliably need to be reproduced to prevent damaging pre-ignitions.

Meeting strict current and future emissions legislation necessitates development of computational tools capable of predicting the behaviour of combustion and emissions with an accuracy sufficient to make correct design decisions while keeping computational cost of the simulations amenable for large-scale design space exploration. While detailed kinetics modelling is increasingly seen as a necessity for accurate simulations, the computational cost can be often prohibitive, prompting interest in simplified approaches allowing fast simulation of reduced mechanisms at coarse grid resolutions appropriate for internal combustion engine simulations in design context. In this study we present a simplified Well-stirred Reactor (WSR) implementation coupled with 3D CFD Ricardo VECTIS solver.

Knocking is one of today’s main limitations in the ongoing efforts to increase efficiency and reduce emissions of spark-ignition engines. Especially for synthetic fuels or any alternative fuel type in general with a much steeper increase of the knock frequency at the KLSA, such as hydrogen, precise knock prediction is crucial to exploit their full potential. This paper therefore proposes a post-processing tool enabling further investigations to continuously gain better understanding of the knocking phenomenon. In this context, evaluation of local auto-ignitions preceding knock is crucial to improve knowledge about the stochastic occurrence of knock but also identify critical engine design to further optimize the geometry. In contrast to 0D simulations, 3D CFD simulations provide the possibility to investigate local parameters in the cylinder during the combustion.

In order to decarbonize and lower the overall emissions of the transport sector, immediate and cost-effective powertrain solutions are needed. Natural gas offers the advantage of a direct reduction of carbon dioxide (CO2) emissions due to its better Carbon to Hydrogen ratio (C/H) compared to common fossil fuels, e.g. gasoline or diesel. Moreover, an optimized engine design suiting the advantages of natural gas in knock resistance and lean mixtures keeping in mind the challenges of power density, efficiency and cold start manoeuvres. In the public funded project MethMag (Methane lean combustion engine) a gasoline fired three-cylinder-engine is redesigned based on this change of requirements and benchmarked against the previous gasoline engine.