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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.

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.

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.

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.

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.

Two substantially different methods have become popular in building fast computing catalyst models: physico-chemical approaches focusing on dimensionality reduction and machine learning approaches. Data driven models are known to be very fast computing and to achieve high accuracy but they can lack of extrapolation capability. Physico-chemical models are usually slower and less accurate but superior regarding robustness. The robustness can even be reinforced by implementing an extended Kalman filter, which enables the model to adapt its states based on actual sensor values, even if the sensors are drifting. The present study proposes a combination of both approaches into one hybrid model, keeping the robustness of the physico-chemical model in edge cases while also achieving the accuracy of the data based model in well-known regimes. The output of the hybrid model is controlled by an autoencoder, utilizing methods well known from the field of anomaly detection.

The paper derives a practical method for analysing transmission rates for light passing through transparent media like outer lenses of head lamps and tail lamps. It is shown that only two geometric parameters are needed to do the analysis, as are the angle of incidence measured to the surface normal and the surface normal itself. The surface is needed to be described mathematically - whether analytical (CAD) or discretised (FE or CFD), but no thickness is necessary. Two fields of application will be shown. The first one is the estimation of light performance or module position of head lamps in the early design process. A second one addresses the optimal time to doing outdoor weathering tests with respect to maximal impact of solar irradiation.

The reduction of both harmful emissions (CO, HC, NOx, etc.) and gases responsible for greenhouse effects (especially CO2) are mandatory aspects to be considered in the development process of any kind of propulsion concept. Focusing on ICEs, the main development topics are today not only the reduction of harmful emissions, increase of thermodynamic efficiency, etc. but also the decarbonization of fuels which offers the highest potential for the reduction of CO2 emissions. Accordingly, the development of future ICEs will be closely linked to the development of CO2 neutral fuels (e.g. biofuels and e-fuels) as they will be part of a common development process. This implies an increase in development complexity, which needs the support of engine simulations. In this work, the virtual modeling of real fuel behavior is addressed to improve current simulation capabilities in studying how a specific composition can affect the engine performance.

CO2 emission constraints taking effect from 2020 lead to further investigations of technologies to lower knock sensitivity of gasoline engines, main limiting factor to increase engine efficiency and thus reduce fuel consumption. Moreover the RDE cycle demands for higher power operation, where fuel enrichment is needed for component protection. To achieve high efficiency, the engine should be run at stoichiometric conditions in order to have better emission control and reduce fuel consumption. Among others, water injection is a promising technology to improve engine combustion efficiency, by mainly reducing knock sensitivity and to keep high conversion rates of the TWC over the whole engine map. The comprehension of multiple thermodynamic effects of water injection through 3D-CFD simulations and their exploitation to enhance the engine combustion efficiency is the main purpose of the analysis.

The consideration of vehicle soiling in the development process becomes ever more important because of the increasing customer demands on current vehicles and the increased use of camera and sensor systems due to autonomous driving. In the process of self-soiling, a soil-water mixture is whirled up by the rotation of the car’s own wheels and deposits on the vehicle surface. The validation of the soiling characteristics in vehicle development usually takes place in an experimental manner, but is increasingly supported by numerical simulations. The droplet field at the tyre has been investigated several times in the past. However, there are no published information regarding the physical background of the droplet formation process and the absolute droplet sizes considering the position at the tyre and the behaviour at different velocities.

Over the past years, the question as to what may be the powertrain of the future has become ever more apparent. Aiming to improve upon a given technology, the internal combustion engine still offers a number of development paths in order to maintain its position in public and private mobility. In this study, an innovative combustion process is investigated with the goal to further approximate the ideal Otto cycle. Thus far, similar approaches such as Homogeneous Charge Compression Ignition (HCCI) shared the same objective yet were unable to be operated under high load conditions. Highly increased control efforts and excessive mechanical stress on the components are but a few examples of the drawbacks associated with HCCI. The approach employed in this work is the so-called Spark Assisted Compression Ignition (SACI) in combination with a pre-chamber spark plug, enabling short combustion durations even at high dilution levels.

Two optical techniques were developed and combined with a CFD simulation to obtain spatio-temporally resolved information on air/fuel mixing in the cylinder of a methane-fueled, fired, optically accessible engine. Laser-induced fluorescence (LIF) of anisole (methoxybenzene), vaporized in trace amounts into the gaseous fuel upstream of the injector, was captured by a two-camera system, providing one instantaneous image of the air/fuel ratio per cycle. Broadband infrared (IR) absorption by the methane fuel itself was measured in a small probe volume via a spark-plug integrated sensor, yielding time-resolved quasi-point information at kHz-rates. The simulation was based on the Reynolds-averaged Navier-Stokes (RANS) approach with the two-equation k-epsilon turbulence model in a finite volume discretization scheme and included the port-fuel injection event. Commercial CFD software was used to perform engine simulations close to the experimental conditions.

Water vapor is, aside from carbon dioxide, the major fossil fuel combustion by-product. Depending on its concentration in the exhaust gas mixture as well as on the exhaust gas pressure, its condensation temperature can be derived. For typical gasoline engine stoichiometric operating conditions, the water vapor dew point lies at about 53 °C. The exhaust gas mixture does however contain some pollutants coming from the fuel, engine oil, and charge air, which can react with the water vapor and affect the condensation process. For instance, sulfur trioxide present in the exhaust, reacts with water vapor forming sulfuric acid. This acid builds a binary system with water vapor, which presents a dew point often above 100 °C. Exhaust composition after leaving the combustion chamber strongly depends on fuel type, engine concept and operation point. Furthermore, the exhaust undergoes several chemical after treatments.

The knowledge of thermal behavior of combustion engines is extremely important e.g. to predict engine warm up or to calculate engine friction and finally to optimize fuel consumption. Typically, thermal engine behavior is modeled using look-up tables or semi-physical models to calculate the temperatures of structure, coolant and oil. Using look-up tables can result in inaccurate results due to interpolation and extrapolation; semi-physical modeling leads to high computation time. This work introduces a new kind of model to calculate thermal behavior of combustion engines using an artificial neural network (ANN) which is highly accurate and extremely fast. The neural network is a multi-layered feed-forward network; it is trained by data generated with a validated semi-physical model. Output data of the ANN-based model are calculated with nonlinear transformation of input data and weighting of these transformations.

The present work involves the technical background of the field of Diesel injection systems of combustion engines and compares the effects of two kinds of remedies (Re-meshing Technique and Linear Interpolation Technique) on mesh deformation. Mathematical formulation of moving grids has been proposed to guide the change of cell volume before. In this study, CFD (Computational Fluid Dynamics) analysis was conducted to study the behaviors of the internal nozzle flow and the characteristics of the spray. An external library concept was introduced to couple the internal nozzle injection process with the spray formation. In addition, all dynamic simulations were performed under a double-axis system. A comparison between simulation and experimental results shows that the integration of the traditional mesh deformation technique with the re-meshing or the linear interpolation technique can repair mesh deformation and further contribute to better simulation results.

Since the mechanisms leading to cyclic combustion variabilities in direct injection gasoline engines are still poorly understood, advanced computational studies are necessary to be able to predict, analyze and optimize the complete engine process from aerodynamics to mixing, ignition, combustion and heat transfer. In this work the Scale-Adaptive Simulation (SAS) turbulence model is used in combination with a parameterized lagrangian spray model for the purpose of predicting transient in-cylinder cold flow, injection and mixture formation in a gasoline engine. An existing CFD model based on FLUENT v15.0 [1] has been extended with a spray description using the FLUENT Discrete Phase Model (DPM). This article will first discuss the validation of the in-cylinder cold flow model using experimental data measured within an optically accessible engine by High Speed Particle Image Velocimetry (HS-PIV).

Two-cylinder engines not only have special demands concerning uniformity and dynamics of oscillating masses and firing order, but also place very different demands on the turbocharger. With two-cylinder engines, the pulsating influence grows and changes the operation of the turbine. In this paper different boosting technologies are compared in small engine applications. Besides turbochargers the potentials and limits of superchargers and electric chargers are compared as well as their combinations. These technologies show differences concerning power supply, operation range and efficiency, and these effects have different implications in small engines. The efficiency of a turbo compressor, for example decreases, rapidly for small dimensions. Results from experiments and engine process simulations are shown based on a two-cylinder engine of 0.8l displacement. The operating condition of a turbocharger turbine in a two-cylinder engine is very specific due to exhaust pulsations.

The aerodynamic optimization of an AUDI Q5 vehicle is presented using the continuous adjoint approach within the OpenFOAM framework. All calculations are performed on an unstructured automatically generated mesh. The primal flow, which serves as input for the adjoint method, is calculated using the standard CFD process at AUDI. It is based on DES calculations using a Spalart-Allmaras turbulence model. The transient results of the primal solution are time averaged and fed to a stationary adjoint solver using a frozen turbulence assumption. From the adjoint model, drag sensitivity maps are computed and measures for drag reduction are derived. The predicted measures are compared to CFD simulations and to wind tunnel experiments at 1:4 model scale. In this context, general challenges, such as convergence and accuracy of the adjoint method are discussed and best practice guidelines are demonstrated.

The optimization of the mixture formation represents great potential to decrease fuel consumption and emissions of spark-ignition engines. The injector and the nozzle are of major importance in this concern. In order to adjust the nozzle geometry according to the requirements an understanding of the physical transactions in the fuel spray is essential. In particular, the primary spray break-up is still described inadequately due to the difficult accessibility with optical measuring instruments. This paper presents a methodology for the characterization of the nozzle-near spray development, which substantially influences the entire spray shape. Single hole injectors of the gasoline direct injection (GDI) with different nozzle hole geometries have been investigated in a high pressure chamber by using the MIE scattering technique. To examine the spray very close to the nozzle exit a long-distance microscope in combination with a Nd:YAG-laser was used.