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The production of electric vehicles (EVs) has a significant environmental impact, with up to 50 % of their lifetime greenhouse gas potential attributed to manufacturing processes. The use of sustainable materials in EV design is therefore crucial for reducing their overall carbon footprint. Wood laminates have emerged as a promising alternative due to their renewable nature. Additionally, wood-based materials offer unique damping properties that can contribute to improved Noise, Vibration, and Harshness (NVH) characteristics. In comparison to conventional materials such as aluminum, ply wood structures exhibit beneficial damping properties. The loss factor of plywood structures with a thickness below 20 mm ranges from 0.013 to 0.032. Comparable aluminum structures however exhibit only a fraction of this loss factor with a range between 0.002 and 0.005.

Expansion chamber mufflers are commonly applied to reduce noise in HVAC. Dissipative materials, such as microperforated plates (MPPs), are often applied to achieve a more broadband mitigation effect. Such mufflers are typically characterized in the frequency domain, assuming time-harmonic excitation. From a computational point of view, transient analyses are more challenging. A transformation of the equivalent fluid model or impedance boundary conditions into the time domain induces convolution integrals. We apply the recently proposed finite element formulation of a time domain equivalent fluid (TDEF) model to simulate the transient response of dissipative acoustic media to arbitrary unsteady excitation. As most time domain approaches, the formulation relies on approximating the frequency-dependent equivalent fluid parameters by a sum of rational functions composed of real-valued or complex-conjugated poles.

In an era characterized by the rapid proliferation and advancement of AI-based technologies across various domains, the spotlight is placed on the integration of these technologies into trustworthy autonomous systems. The integration into embedded systems necessitates a heightened focus on dependability. This paper combines the findings from the TEACHING project, which delves into the foundations of humanistic AI concepts, with insights derived from an expert workshop in the field of dependability engineering. We establish the body of knowledge and key findings deliberated upon during an expert workshop held at an international conference focused on computer safety, reliability and security. The dialogue makes it evident that despite advancements, the assurance of dependability in AI-driven systems remains an unresolved challenge, lacking a one-size-fits-all solution.

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.

As alternative to electrification or carbon free fuels such as hydrogen, CO2-neutral fuels have been researched aiming to decrease the impact of fossil energy sources on the environment. Despite the potential benefit of capturing CO2 emission after combustion for own fuel production, the so-called eFuels also benefit by using a green source of energy during their fabrication. Among all the possibilities for eFuels, alcohols, ethers (such as MTBE and ETBE) and alternative hydrocarbons have shown positive impacts regarding emission reduction and performance when compared to standard gasoline. Previously in [1] and [2], synthetic fuels and methanol blends were tested at steady state conditions in order to verify advantages and drawbacks relative to gasoline, for power-sport motorcycles.

Currently, emission regulations for the LVs using standard spark ignited ICEs considering only gaseous pollutants, just as CO, HC and NOx. Following the upcoming legislation for personal vehicles sector, the LVs might also include limits of PN and PM. Regarding fuel injection strategies, the MPFI which was previously excluded from particulate control will be incorporated into the new regulation [1]. In terms of social harm, there will be a necessity to reduce engine particulate emissions, as they are known for being carcinogenic substances [2, 3, 4]. Generally, the smaller the particulate diameter, the more critical are the damages for human health therefore, the correct determination of PN and particulate diameter is essential. Beside future challenges for reducing and controlling particulates, the reduction of fossil fuel usage is also an imminent target, being the replacement by eFuels one of the most promising alternatives.

To achieve global climate goals, greenhouse gas emissions must be drastically reduced. The energy and transportation sectors are responsible for about one third of the greenhouse gases emitted worldwide, and they often use internal combustion engines (ICE). One effective way to decarbonize ICEs may be to replace carbon-containing fossil fuels such as natural gas entirely, or at least partially, with hydrogen. Cost-effective development of sustainable combustion concepts for hydrogen and natural gas/hydrogen mixtures in ICEs requires the intensive use of fast and robust simulation tools for prediction. The key challenge is appropriate modeling of flame front propagation. This paper evaluates and applies different approaches to modeling laminar flame speeds from the literature. Both appropriate models and reaction kinetic calculations are considered.

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.

On the basis of small hybrid powertrain investigations in hand-held power tools for fuel consumption and emissions reduction, the prototype hybrid configuration of a small single-cylinder four-stroke internal combustion engine together with a brushless DC electric motor is built and measured on the testbench in terms of efficiency and emissions but also torque and power capabilities. The onboard energy storage system allows the combustion engine electrification for controlling the fuel amount and the combustion behavior while the electric motor placement instead of the pull-start and flywheel allows for start-stop of the system and load point shifting strategy for lower fuel consumption. The transient start-up results as well as the steady-state characterization maps of the system can set the limits on the fuel consumption reduction for such a hybrid tool compared with the baseline combustion-driven tool for given load cycle characteristics.

Virtual sensing refers to the processing of desired physical data based on measured values. Virtual sensors can be applied not only to obtain physical quantities which cannot be measured or can only be measured at an unreasonable expense but also to reduce the number of physical sensors and thus lower costs. In the field of spark ignited internal combustion engines, the virtual sensing approach may be used to predict the cylinder pressure signal (or characteristic pressure values) based on the acceleration signal of a knock sensor. This paper presents a method for obtaining the cylinder pressure signal in the high-pressure phase of an internal combustion engine based on the measured acceleration signal of a knock sensor. The approach employs a partial differential equation to represent the physical transfer function between the measured signal and the desired pressure. A procedure to fit the modeling constants is described using the example of a large gas engine.

In the ongoing competition of powertrain concepts the Internal Combustion Engine (ICE) will also have to demonstrate its potential for increased efficiency [1]. Variable Compression Ratio (VCR) Systems for Internal Combustion Engines (ICE) can make an important contribution to meeting stringent global fuel economy and CO2 standards. Using such technology a CO2 reduction of between 5% and 9% in the World Harmonized Light-Duty Vehicle Test Cycle (WLTC) are achievable, depending on vehicle class, load profile and power rating [2]. This paper provides a detailed description of the measurement approaches that are used during development of the AVL Dual Mode VCSTM and other VCR systems in fired operation. Results obtained from these measurements are typically used to calibrate or verify simulation models, which themselves are an integral part of the development of these systems [3].

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.

Aerodynamic CFD simulations in the automotive industry, which are based on the steady-state RANS (Reynolds-averaged Navier-Stokes) approach typically utilize approximate numerical methods to account for rotating wheels. In these methods, the computational mesh representing the rim geometry remains stationary, and the influence of the wheel rotation on the air flow is modelled. As the rims are considered only in one fixed rotational position (chosen arbitrarily in most cases), the effects of the rim orientation on the aerodynamic simulation results are disregarded and remain unquantified. This paper presents a numerical sensitivity study to examine the impact of the rim orientation position on the aerodynamic parameters of a detailed production vehicle. The simulations are based on the steady-state RANS approach.

High-pressure direct injection (HPDI) of natural gas into the combustion chamber enables a non-premixed combustion regime known from diesel engines. Since knocking combustion cannot occur with this combustion process, an increase in the compression ratio and thus efficiency is possible. Due to the high injection pressures required, this concept is ideally suited to applications where liquefied natural gas (LNG) is available. In marine applications, the bunkering of and operation with LNG is state-of-the-art. Existing HPDI gas combustion concepts typically use a small amount of diesel fuel for ignition, which is injected late in the compression stroke. The diesel fuel ignites due to the high temperature of the cylinder charge. The subsequently injected gas ignites at the diesel flame. The HPDI gas combustion concept presented in this paper is of a monovalent type, meaning that no fuel other than natural gas is used.

Due to current progresses in the field of driver assistance systems and the continuously growing electrification of vehicle drive trains, the evaluation of driver behavior has become an important part in the development process of modern cars. Findings from driver analyses are used for the creation of individual profiles, which can be permanently adapted due to ongoing data processing. A benefit of data-based dynamic control systems lies in the possibility to individually configure the vehicle behavior for a specific driver, which can contribute to increasing customer acceptance and satisfaction. In this way, an optimization of the control behavior between driver and vehicle and the resulting mutual system learning and -adjustment hold great potential for improvements in driving behavior, safety and energy consumption.