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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.

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.

Hydrogen engines are currently considered as a viable solution to preserve the internal combustion engine as a power unit for vehicle propulsion. In particular, lean-burn gasoline Spark-Ignition (SI) engines have been a major subject of investigations due to the reduced emission levels and high thermodynamic efficiency. This strategy is suitable for the purpose of passenger car applications and cannot be tailored in the field of high performance engine, where the air mass delivered would require oversized turbocharging systems or more complex charging solutions. For this reason, the range of stoichiometric feeding condition is explored in the high performance engine, leading to the consequent issue of abatement of pollutant emissions. In this work a 1D model will be applied to the modeling of a V8 engine fueled with DI of hydrogen. The engine has been derived by a gasoline configuration and adapted to hydrogen in such a way to keep the same performance.

By analyzing the dynamic distortion in all body closure openings in a complete vehicle, a better understanding of the body characteristics can be achieved compared to traditional static load cases such as static torsional body stiffness. This is particularly relevant for non-traditional vehicle layouts and electric vehicle architectures. The body response is measured with the so-called Multi Stethoscope (MSS) when driving a vehicle on a rough pavé road (cobble stone). The MSS is measuring the distortion in each opening in two diagonals. During the virtual development, the distortion is described by the relative displacement in diagonal direction in time domain using a modal transient analysis. The results are shown as Opening Distortion Fingerprint ODF and used as assessment criteria within Solidity and Perceived Quality. By applying the Principal Component Analysis (PCA) on the time history of the distortion, a Dominant Distortion Pattern (DDP) can be identified.

Given the growing interest in improving the efficiency of the bus fleet in public transportation systems, this paper presents an analysis of the energy consumption of a battery electric bus. During the experimental campaign, a battery electric bus was loaded using sand payloads to simulate the passenger load on board and followed another bus during regular service. Data related to the energy consumed by various bus utilities were published on the vehicle’s CAN network using the FMS standard and sampled at a frequency of 1 Hz. The collected experimental data were initially analyzed on a daily basis and then on a per-route basis. The results reveal the breakdown of energy consumption among various utilities over the course of each day of the experiment, highlighting those responsible for the highest energy consumption.

Polymer electrolyte membrane (PEM) fuel cells will play a crucial role in the decarbonization of the transport sector, in particular for heavy duty applications. However, performance and durability of PEMFC stacks is still a concern especially when operated under high power density conditions, as required in order to improve the compactness and to reduce the cost of the system. In this context, the optimization of the geometry of hydrogen and air distributors represents a key factor to improve the distribution of the reactants on the active surface, in order to guarantee a proper water management and avoiding membrane dehydration.

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.

Roundabouts are intersections at which automated cars seem currently not performing sufficiently well. Actually, sometimes, they get stuck and the traffic flow is seriously reduced. To overcome this problem a V2N-N2V (vehicle-to-network-network-to-vehicle) communication scheme is proposed. Cars communicate via 5G with an edge computer. A cooperative machine-learning algorithm orchestrates the traffic. Automated cars are instructed to accelerate or decelerate with the triple aim of improving the traffic flow into the roundabout, keeping safety constraints, and providing comfort for passengers on board of automated vehicles. In the roundabout, both automated cars and human-driven cars run. The roundabout scenario has been simulated by SUMO. Additionally, the scenario has been reconstructed into a dynamic driving simulator, with a real human driver in a virtual reality environment. The aim was to check the human perception of traffic flow, driving safety and driving comfort.

The abatement of carbon dioxide and pollutant emissions on motorbike spark-ignition (SI) engines is a challenging task, considering the small size, the low cost and the high power-to-weight ratio required by the market for such powertrain. In this context, the passive pre-chamber (PPC) technology is an attractive solution. The combustion duration can be reduced by igniting the air-fuel mixture inside a small volume connected to the cylinder, unfolding the way to high engine efficiencies without penalization of the peak performance. Moreover, no injectors are needed inside the PPC, guaranteeing a cheap and fast retrofitting of the existing fleet. In this work, a 3D computational fluid dynamics (CFD) investigation is carried out over an experimental configuration of motorbike SI engine, operated at fixed operating conditions with both traditional and PPC configurations.

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.

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.

Air pollution is a significant environmental issue, and exhaust emissions from internal combustion engines are one of the primary sources of harmful pollutants. The transportation sector, which includes road vehicles, contributes to a large share of these emissions. In Europe, the latest emission legislation (Euro 7) proposes more stringent limits and testing conditions for vehicle emissions. To meet these limits, the automotive industry is actively developing innovative exhaust emission-control technologies. With the growing prevalence of electrification, internal combustion engines are subject to continuous variations in load and engine speed, including phases where the engine is switched off. The result is an operating condition characterized by successive cold starts. In this context, the challenge in coping with the emission limits is to minimize the light-off time and prevent fast light-out conditions during idling or city driving.

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.

Charge dilution in gasoline engines reduces NOx emissions and wall heat losses by the lower combustion temperature. Furthermore, under part load conditions de-throttling allows the reduction of pumping losses and thus higher engine efficiency. In contrast to lean burn, charge dilution by exhaust gas recirculation (EGR) under stoichiometric combustion conditions enables the use of an effective three-way catalyst. A pre-chamber spark plug with hot surface-assisted spark ignition (HSASI) was developed at the UAS Karlsruhe to overcome the drawbacks of charge dilution, especially under part load or cold start conditions, such as inhibited ignition and slow flame speed, and to even enable a further increase of the dilution rate. The influence of the HSASI pre-chamber spark plug on the heat release under EGR dilution and stoichiometric conditions was investigated on a single-cylinder gasoline engine.

Particulates are among the most harmful emission components of internal combustion engines (ICE)). Thus, emission limits have been widely introduced, e.g., for light- and heavy-duty vehicles. Although there are still engine applications without particulate limitations, the measurement of particulate mass (PM) and particulate number (PN) emissions is therefore of special interest for the development and operation of ICE. For this purpose, a measurement system for PN consisting of a custom-built sample conditioning and dilution system, and a TSI 3790-A10 [1] condensation particle counter (CPC) as particle number counter (PNC) was designed and built. In this work, we present the conditioning and dilution system, the operational parameters, and results from the particle concentration reduction factor (PCRF) calibration.

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.

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.

The objective of this experimental investigation was to analyze the effect of various exhaust gas aftertreatment technologies on particulate number emissions (PN) of an MPFI EU5 motorcycle. Specifically, three different aftertreatment strategies were compared, including a three-way-catalyst (TWC) with LS structure as the baseline, a hybrid catalyst with a wire mesh filter, and an optimized gasoline particulate filter (GPF) with three-way catalytic coating. Experimental investigations using the standard test cycle WMTC performed on a two-wheeler chassis dynamometer, while the inhouse particulate sampling system was utilized to gather information about size-dependent filtering efficiency, storage, and combustion of nanoparticles. The particulate sampling and measuring system consist of three condensation particle counters (CPCs) calibrated to three different size classes (SPN4, SPN10, SPN23).

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.

In order to combat the predicted consequences of climate change, major efforts are required in all industries. The use of hydrogen in combustion engines can make a valuable contribution as a CO2-free bridging technology. A challenge in the development of a suitable combustion process is the high ignitibility of hydrogen with an impact on combustion stability due to combustion anomalies. The avoidance of such combustion phenomena is of the highest relevance for ensuring long-term stable engine operation as far as possible. The present paper deals with the multifractional topic of abnormal combustion phenomena in the hydrogen engine.