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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.

The safety of BEVs in driving, charging and parking condition is essential for the success of electrification in automotive industry as well as key driver of any future development of Li-Ion HV battery. AVL has developed a unique simulation approach in which the multi-physical behavior of the single cell in thermal runaway is modelled and applied to module, pack or vehicle level. In addition and beside this cell behavior, various more physical phenomena during thermal propagation on pack level are considered and predicted by the simulation method: component melting, ignition and flammibilty of venting gas and HV failures.

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.

In this paper, the multi-physical simulation workflow from electromagnetics to structural dynamics for a squirrel-cage induction machine is explored. In electromagnetic simulations, local forces and rotor torque are calculated for specific speed-torque operation points. In order to consider non-linearities and interaction with control system as well as transmission, time-domain simulations are carried out. For induction machines, the computational effort with full transient numerical methods like finite element analysis (FEA) is very high. A novel reduced order electro-mechanical model is presented. It still accounts for vibro-acoustically relevant harmonics due to pulse-width modulation (PWM), slotting, distributed winding and saturation effects, but is substantially faster (minutes to hours instead of days to weeks per operation point).

Wet Clutches are used in automotive powertrains to enable compact designs and efficient gear shifting. During the slip phase of engagement, significant flash temperatures arise at the friction disc to separator interface because of dissipative frictional losses. An important aspect of the design process is to ensure the interface temperature does not exceed the material temperature threshold at which accelerated wear behavior and/or thermal degradation occurs. During the early stages of a design process, it is advantageous to evaluate numerous system and component design iterations exposed to plethora of possible drive cycles. A simulation tool is needed which can determine the critical operational conditions the system must survive for performance and durability to be assured. This paper describes a time-efficient multiphysics model developed to predict clutch disc temperatures with a runtime in the order of minutes.

To avoid frequent regeneration intervals leading to expeditious ageing of the catalyst and substantial fuel penalty for the owner, it is always desired to estimate the soot coming from diesel exhaust emission, the soot accumulated and burnt in the Diesel Particulate Filter (DPF). Certain applications and vehicle duty cycles cannot make use of the differential pressure sensor for estimating the soot loading in the DPF because of the limitations of the sensor tolerance and measurement accuracy. The physical soot model is always active and hence a precise and more accurate model is preferred to calibrate & optimize the regeneration interval. This paper presents the approach to estimate the engine-out soot and the accumulated soot in the DPF using a graphical calculation tool (AVL Concerto CalcGraf™).

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

The latest generation of internal combustion engines may emit significant levels of sub-23 nm particles. The main objective of the Horizon 2020 “DownToTen” project was to develop a robust methodology and provide policy recommendations towards the particle number (PN) emissions measurements in the sub-23 nm region. In order to achieve this target, a new portable exhaust particle sampling system (PEPS) was developed, being capable of measuring exhaust particles down to at least 10 nm under real-world conditions. The main design target was to build a system that is compatible with current PMP requirements and is characterized by minimized losses in the sub-23 nm region, high robustness against artefacts and high flexibility in terms of different PN modes investigation, i.e. non-volatile, volatile and secondary particles.

Fuel injection is a key process influencing the performance of Gasoline Direct Injection (GDI) Engines. Injecting fuel at elevated temperature can initiate flash boiling which can lead to faster breakup, reduced penetration, and increased spray-cone angle. Thus, it impacts engine efficiency in terms of combustion quality, CO2, NOx and soot emission levels. This research deals with modelling of flash boiling processes occurring in gasoline fuel injectors. The flashing mass transfer rate is modelled by the advanced Hertz-Knudsen model considering the deviation from the thermodynamic-equilibrium conditions. The effect of nucleation-site density and its variation with degree of superheat is studied. The model is validated against benchmark test cases and a substantiated comparison with experiment is achieved.

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.

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.

In the context of today’s and future legislative requirements for NOx and soot particle emissions as well as today’s market trends for further efficiency gains in gasoline engines, computational fluid dynamics (CFD) models need to further improve their intrinsic predictive capability to fulfill OEM needs towards the future. Improving fuel chemistry modelling, knock predictions and the modelling of the interaction between the chemistry and turbulent flow are three key challenges to improve the predictivity of CFD simulations of Spark-Ignited (SI) engines. The Flamelet Generated Manifold (FGM) combustion modelling approach addresses these challenges. By using chemistry pre-tabulation technologies, today’s most detailed fuel chemistry models can be included in the CFD simulation. This allows a much more refined description of auto-ignition delays for knock as well as radical concentrations which feed into emission models, at comparable or even reduced overall CFD run-time.

In contrast to the well-established “standard” log-law wall function, the analytical wall function (AWF) as an advanced modelling approach has not been extensively used in the industrial computational fluid dynamics (CFD) applications. As the model was originally developed aiming at computations on relatively coarse meshes, potential stability issues may arise due to the pressure-gradient sensitivity if employing locally inappropriate mesh layers, typically associated with the complex geometry details. This work evaluates performance of the thermal AWF, as proposed by Suga [4], in conjunction with the main flow field computed employing the k-ζ-f turbulence model and the hybrid wall treatment (denoted as AWF-e) within the Reynolds-averaged Navier-Stokes (RANS) framework.

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.

With upcoming emission regulations particle emissions for GDI engines are challenging engine and injector developers. Despite the introduction of GPFs, engine-out emission should be optimized to avoid extra cost and exhaust backpressure. Engine tests with a state of the art Miller GDI engine showed up to 200% increased particle emissions over the test duration due to injector deposit related diffusion flames. No spray altering deposits have been found inside the injector nozzle. To optimize this tip sooting behavior a tool chain is presented which involves injector multiphase simulations, a spray simulation coupled with a wallfilm model and testing. First the flow inside the injector is analyzed based on a 3D-XRay model. The next step is a Lagrangian spray simulation coupled with a wallfilm module which is used to simulate the fuel impingement on the injector tip and counter-bores.