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In electrified vehicles, auxiliary units can be a dominant source of noise, one of which is the refrigerant scroll compressor. Compared to vehicles with combustion engines, e-vehicles require larger refrigerant compressors, as in addition to the interior, also the battery and the electric motors have to be cooled. Currently, scroll compressors are widely used in the automotive industry, which generate one pressure pulse per revolution due to their discontinuous compression principle. This results in speed-dependent pressure fluctuations as well as higher-harmonic pulsations that arise from reflections. These fluctuations spread through the refrigeration cycle and cause the vibration excitation of refrigerant lines and heat exchangers. The sound transmission path in the air conditioning heat exchanger integrated in the dashboard is particularly critical. Various silencer configurations can be used to dampen these pulsations.

Cybersecurity assumes a major role in the context of the automotive domain, where both existing and forthcoming regulations are heightening the need for robust security engineering. A significant milestone in advancing cybersecurity within the automotive industry is the release of the first international standard for automotive cybersecurity ISO/SAE 21434:2021 ‘Road Vehicles — Cybersecurity Engineering’. A recently published type approval regulation for automotive cybersecurity (UN R155) is also tailored for member countries of the UNECE WP.29 alliance. Thus, the challenges for embedded automotive systems engineers are increasing while frameworks, tools and shared concepts for cybersecurity engineering and training are scarce.

Brake wear emissions gained significant relevance with the upcoming Euro7 type approval within the European Union for brake emission measurement on the test bed. While the controlled brake test bed approach provides consistent results, real-driving emission (RDE) measurements are needed to better understand actual emission behavior due to varying vehicle and environmental conditions. The EU has already announced its interest in RDE testing. Here we present the results of an RDE brake wear sampling system with minimal thermal impact, where particles are only sampled from one side of the brake disc, characterized on a laboratory sampling system. The investigations aim to validate symmetric particle release and to confirm that doubling the measured RDE results effectively represents the reference emissions on the test bed.

In battery electric vehicles (BEV), thermal management is a key technique to improve efficiency and lifetime. Currently, manufacturers use different cooling concepts with numerous architectures. This work describes the development of a co-simulation framework to optimize BEV thermal management on system level, using advanced simulation methodologies also on component level, merging simulation and testing. Due to interactions between multiple conditioning circuits, thermal management optimization requires an overall vehicle approach. Thus, a full vehicle co-simulation of a BEV is developed, combining 1D thermal management software KULI and MATLAB/Simulink. Within co-simulation, the precise modeling of vehicle’s subsystems is important to predict thermal behavior and to calculate dynamic heating and cooling demands as well as exchanged energy flows with the thermal management system.

Virtual sensing, i.e., the method of estimating quantities of interest indirectly via measurements of other quantities, has received a lot of attention in various fields: Virtual sensors have successfully been deployed in intelligent building systems, the process industry, water quality control, and combustion process monitoring. In most of these scenarios, measuring the quantities of interest is either impossible or difficult, or requires extensive modifications of the equipment under consideration – which in turn is associated with additional costs. At the same time, comprehensive data about equipment operation is collected by ever increasing deployment of inexpensive sensors that measure easily accessible quantities. Using this data to infer values of quantities which themselves are impossible to measure – i.e., virtual sensing – enables monitoring and control applications that would not be possible otherwise.

In this paper, we will show the potentials of reducing NOx emissions of an H2-ICE to an ultra-low level by hybridizing the H2-ICE in an NRMM powertrain. Real-world measurement data of NRMM together with a simulated hybrid powertrain and operating strategy form the input data for the H2-ICE on the test bench. We have modified a turbocharged four-cylinder in-line gasoline engine for use with directly injected hydrogen. Within several iteration loops, we obtained measurement data that shows that, depending on the operating strategy, ultra-low NOx emissions are reachable. The combination of hybridization, which implies the possibility of recuperation, and the CO2 emission-free H2-ICE leads to a highly efficient, robust, and economic drivetrain with the lowest emissions, perfectly suitable for Non-Road Machinery. Additionally, we will discuss the overall coupled measurement and simulation setup and the reachable NOx emission levels in our tested setup.

Precise prediction of combustion parameters such as peak firing pressure (PFP) or crank angle of 50% burned mass fraction (MFB50) is essential for optimal engine control. These quantities are commonly determined from in-cylinder pressure sensor signals and are crucial to reach high efficiencies and low emissions. Highly accurate in-cylinder pressure sensors are only applied to test rig engines due to their high cost, limited durability and special installation conditions. Therefore, alternative approaches which employ virtual sensing based on signals from non-intrusive sensors retrieved from common knock sensors are of great interest. This paper presents a comprehensive comparison of selected approaches from literature, as well as adjusted or further developed methods to determine engine combustion parameters based on knock sensor signals. All methods are evaluated on three different engines and two different sensor positions.

As a result of the ever-increasing application of cyber-physical components in the automotive industry, cybersecurity has become an urgent topic. Adapting technologies and communication protocols like Ethernet and WiFi in connected vehicles yields many attack scenarios. Consequently, ISO/SAE 21434 and UN R155 (2021) define a standard and regulatory framework for automotive cybersecurity, Both documents follow a risk management-based approach and require a threat modeling methodology for risk analysis and identification. Such a threat modeling methodology must conform to the Threat Analysis and Risk Assessment (TARA) framework of ISO/SAE 21434. Conversely, existing threat modeling methods enumerate isolated threats disregarding the vehicle’s design and connections. Consequently, they neglect the role of attack paths from a vehicle’s interfaces to its assets.

Brake wear particles are recognized as one of the dominant sources of road transport particulate matter emissions and are linked to adverse health effects and environmental impact. The UNECE mandated the Particle Measurement Program to address this issue, by developing a harmonized sampling and measurement methodology for the investigation of brake wear particles on a brake dynamometer (dyno). However, although the brake dyno approach with tightly controlled test conditions offers good reproducibility, a multitude of changing vehicle and surrounding conditions make real-driving emissions measurement a highly relevant task. Here we show two different prototypes for on-road particle measurement with minimal impact of the measurement setup on the emission behavior, tested on a brake dyno.

The current European fleet of vehicles is ageing and lifetime mileages are rising proportionally. Consequently, a substantial fraction of the vehicle fleet is currently operating at mileages well beyond current durability legislation (≤ 160,000 km). Emissions inventories and models show substantial increases in emissions with increasing mileage, but knowledge of the effect of emissions control system deterioration at very high mileages is sparse. Emissions testing has been conducted on matched pairs (or more) of diesel and gasoline (and CNG) vehicles, of low and high mileage, supplementing the results with in-house data, in order to explore high mileage emission deterioration factors (DF). The study isolated, as far as possible, the effect of emissions deterioration with mileage, by using nominally identical vehicle models and controlling other variables.

In the acoustic design of flow guiding components, novel simulation concepts for predicting relevant sound sources in the early design state become increasingly important. This requires accurate numerical methods to describe the involved phenomena. The present study computationally investigates the flow-induced aeroacoustic sound sources, generated in turbulent pipe flow. The analysis follows a hybrid approach, where the acoustic sound field is predicted separately from the underlying turbulent flow field, supplied with acoustic source terms from an incompressible flow simulation of the considered configuration in the limit of low Mach number. Source terms for use as input into different acoustic wave equations, the Lighthill wave equation, the vortex sound theory, and the Perturbed Convective Wave Equation (PCWE) are computed performing incompressible Direct Numerical Simulations (DNS) and Large-Eddy Simulations (LES) of fully developed pipe flow.

The demand for high efficiency powertrains in automotive engineering is further increasing, with hybrid powertrains being a feasible option to cope with new legislations. So far hybridization has only played a minor role for L-category vehicles. Focusing on an exemplary high-power L-category on-road vehicle, this research aims to show a new development approach, which combines longitudinal dynamic simulation (LDS) with “Design of Experiments” (DoE) in course of hybrid electric powertrain development. Furthermore, addressing the technological aspect, this paper points out how such a vehicle can benefit from 48V-hybridization of its already existing internal combustion powertrain. A fully parametric LDS model is built in Matlab/Simulink, with exchangeable powertrain components and an adaptable hybrid operation strategy. Beforehand, characterizing decisions as to focus on 48V and on parallel hybrid architecture are made.

Drivetrain electrification is increasing in the kart racing sector since noise emissions are an important factor in urban areas. To improve range, it has become necessary to optimize the rolling resistance of kart racing tires. This paper introduces a parameter study for small bias-ply tires which are used in kart racing and investigates the effect of these parameters on rolling resistance. In recent literature, rolling resistance is mostly examined in radial passenger car tires. Most testing devices are limited to rim sizes from ten inches upwards. In this study, a test rig was developed with focus on low cost and small rim sizes. This self-developed test rig was validated through a comparison with an approved test rig according to ISO 18164 standard. A parameter study was conducted to investigate the effect of changes in the construction of the tire. These changes affect the warp count of the carcass fabric and the crown angle of the different plies.

In-cylinder flows in internal combustion engines are highly turbulent in nature. An important property of turbulence that plays a key role in mixture formation is anisotropy; it also influences ignition, combustion and emission formation. Thus, understanding the turbulence anisotropy of in-cylinder flows is critical. Since the most widely used two-equation Reynolds-averaged Navier-Stokes (RANS) turbulence models assume isotropic turbulence, they are not suitable for correctly capturing the anisotropic behavior of turbulence. However, large eddy simulation (LES) can account for the anisotropic behavior of turbulence. In this paper, the Reynolds stress tensor (RST) is analyzed to assess the predictive capability of RANS and LES with regard to turbulence anisotropy. The influence of mesh size on turbulence anisotropy is also looked into for multi-cycle LES.

In industrial processes and other power generation processes, large amounts of waste heat are often lost to the environment. The conversion of this thermal energy into mechanical work promises a significant improvement in energy-utilization, the efficiency of the overall system and, consequently, cost-effectiveness. Therefore, the use of a Rankine-Cycle is a well-established technical process. A recent research project has investigated a novel expansion machine to be integrated into such an RC-process. Primarily, the present work deals with the fluid dynamic simulation of this expander, which is based on the principle of a rotary piston engine. The aim is to develop, analyze and optimize the process and the corresponding components. Hence, a CFD-model had to be built up, which should correspond as closely as possible to the physical engine.

Amid the increasing demand for higher efficiency in combustion driven handheld tools, the recent developments in electric machine technology together with the already existing benefits of small combustion engines for these applications favor the investigation of potential advantages in hybrid powertrain tools. This concept-design study aims to use a fully parametric, system-level simulation model with exchangeable blocks, created with a power-loss approach in Matlab and Simulink, in order to examine the potential of different hybrid configurations for different tool load cycles. After the model introduction, the results of numerous simulations for 36 to 100 cc engine displacement will be presented and compared in terms of overall system efficiency and overall powertrain size. The different optimum hybrid configurations can show a reduction up to 30 % in system’s brake specific fuel consumption compared to the baseline combustion engine driven model.

The absence of combustion engine noise pushes increasingly attention to the sound generation from other, even much weaker, sources in the acoustic design of electric vehicles. The present work focusses on the numerical computation of flow induced noise, typically emerging in components of flow guiding devices in electro-mobile applications. The method of Large-Eddy Simulation (LES) represents a powerful technique for capturing most part of the turbulent fluctuating motion, which qualifies this approach as a highly reliable candidate for providing a sufficiently accurate level of description of the flow induced generation of sound. Considering the generic test configuration of turbulent pipe flow, the present study investigates in particular the scope and the limits of incompressible Large-Eddy Simulation in predicting the evolution of turbulent sound sources to be supplied as source terms into the acoustic analogy of Lighthill.

Creep groan is an annoying brake noise at very low speeds of the vehicle. In general, stick-slip between brake disk and brake pads is believed to be the most dominating vibration mechanism of creep groan phenomena. This paper will show by sophisticated measurement techniques that stick-slip and speed-dependent friction is an important trigger. However, the overall vibration is much more complex than stick-slip reproduced by simple conveying belt minimal models. It turns out that in typical brake systems of passenger cars, creep groan appears from 15 to 25 Hz as well as 60 to 100 Hz. The mechanism from 15 to 25 Hz is highly impulsive and “hard”. Transitions between stick and slip phases trigger coupled nonlinear vibrations of the complete brake and suspension system. From 60 to 100 Hz, the vibrations show a more harmonic-like and “soft” signature, caused mainly by a speed-dependent friction behavior.

Turbulence anisotropy has a great influence on mixture formation and flame propagation in internal combustion engines. However, the visualization of turbulence in simulations is not straightforward; traditional methods lack the ability to display the anisotropic properties in the engine geometry. Instead, they use invariant maps, and important information about the locality of the turbulence anisotropy is lost. This paper overcomes this shortcoming by visualizing the anisotropy directly in the physical domain. Componentality contours are applied to directly visualize the anisotropic properties of turbulence in the three-dimensional engine geometry. Using an RGB (red, green, blue) color map, the three limiting states of turbulence (one-component, axisymmetric two-component and isotropic turbulence) are displayed in the three-dimensional physical domain.

The upstream flow conditions and the use of tractive power to accelerate a vehicle are both sources of energy loss. The vehicle speed and the upstream flow conditions result in the oncoming wind vector experienced by the moving vehicle. The aim of the present work is to show a new approach to consider the chaotic and random behavior of surrounding flow conditions and their influence on driving performance. The approach is shown for the example of motorbike racing conditions. Special interest was put on a description of the flow conditions with respect to well know turbulent flow field parameters like the turbulent length scale or the turbulence intensity. Depending on where the flow conditions are measured, stationary in the earth reference frame, or on a moving vehicle, it is quite difficult to get a robust description of the flow field parameters. These parameters are used together with the Reynolds number to predict the aerodynamic behavior by correlation functions or maps.