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Opposed-piston two-stroke engines offer numerous advantages over conventional four-stroke engines, both in terms of fundamental principles and technical aspects. The reduced heat losses and large volume-to-surface area ratio inherently result in a high thermodynamic efficiency. Additionally, the mechanical design is simpler and requires fewer components compared to conventional four-stroke engines. When combining this engine concept with alternative fuels such as hydrogen and pre-chamber technology, a potential route for carbon-neutral powertrains is observed. To ensure safe engine operation using hydrogen as fuel, it is crucial to consider strict safety measures to prevent issues such as knock, pre-ignition, and backfiring. One potential solution to these challenges is the use of direct injection, which has the potential to improve engine efficiency and expand the range of load operation.

When using "green" hydrogen, fuel cell technology plays a key role in emission-free mobility. A powertrain based on fuel cells (FC) shows its advantages over battery-electric powertrains when the requirement profile primarily demands high performance over a longer period of time, high flexible availability and short refueling times. In addition, FC achieves higher effi-ciencies than the combustion of hydrogen in a gas engine, meaning that the chemical energy is used more efficiently than with established combustion engines. When using FC technology, numerous companies in Baden-Württemberg can contribute their specific expertise from the traditional automotive construction and supplier business. This includes auxiliary units in the air (cathode) and hydrogen (anode) path, such as the air com-pressor, the H2 recycling pump, humidifier, cooling system, power electronics, valve and pressure tank technology as well as components of the fuel cell stack itself.

Due to its physical and chemical properties, hydrogen is an attractive fuel for internal combustion engines, providing grounds for studies on hydrogen engines. It is common practice to use a mathematical model for basic engine design and an essential part of this is the simulation of the combustion cycle, which is the subject of the work presented here. One of the most widely used models for describing combustion in gasoline and diesel engines is the Wiebe model. However, for cases of hydrogen combustion in DI engines, which are characterized by mixture stratification and in some cases significant incomplete combustion, practically no data can be found in the literature on the application of the Wiebe model. Based on Wiebe's formulas, a mathematical model of hydrogen combustion has been developed. The model allows making computations for both DI and PFI hydrogen engines. The parameters of the Wiebe model were assessed for three different engines in a total of 26 operating modes.

The hydrogen engine is one of the promising technologies that enables carbon-neutral mobility, especially in heavy-duty on- or off-road applications. In this paper, a methodological procedure for the design of the combustion system of a hydrogen-fueled, direct injection spark ignited commercial vehicle engine is described. In a preliminary step, the ability of the commercial 3D computational fluid dynamics (CFD) code AVL FIRE classic to reproduce the characteristics of the gas jet, introduced into a quiescent environment by a dedicated H2 injector, is established. This is based on two parts: Temporal and numerical discretization sensitivity analyses ensure that the spatial and temporal resolution of the simulations is adequate, and comparisons to a comprehensive set of experiments demonstrate the accuracy of the simulations. The measurements used for this purpose rely on the well-known schlieren technique and use helium as a safe substitute for H2.

Nowadays, green hydrogen can play a crucial role in a successful clean energy transition, thus reaching net zero emissions in the transport sector. Moreover, hydrogen exploitation in internal combustion engines is favoured by its suitable combustion properties and quasi-zero harmful emissions. High flame speeds enable a lean combustion approach, which provides high efficiency and reduces NOx emissions. However, high air flow rates are required to achieve the load levels typical of heavy-duty applications. In this framework, the present study aims to investigate the required boosting system of a 6-cylinder, 13-liter heavy-duty spark ignition engine through 1D numerical simulation. A comparison among various architectures of the turbocharging system and the size of each component is presented, thus highlighting limitations and potentialities of each architecture and providing important insights for the selection of the best turbocharging system.

The Single Cylinder Research Engine (SCRE) at the Institute of Internal Combustion Engines and Powertrain Systems is equipped with a variable valve train that allows to switch between regular intake valve lift and early intake valve closing (Miller). On the exhaust side, a secondary valve lift on each valve is possible with adjustable back pressure and thus the possibility of realising internal EGR. In combination with alternative fuels, even if they are Drop-In capable as HVO, properties differ and can influence the emission and efficiency behaviour. The investigations of this paper are focusing on regenerative Drop-In fuel (HVO), fossil fuel (B7), and an oxygenate (OME), that needs adaptions at the engine control unit, but offers further emission potential. By commissioning a 2-stage boost system, it is possible to fully equalize the air mass in Miller mode compared to the normal valve lift.

Ducted Fuel Injection (DFI) engines have emerged as a promising technology in the pursuit of a clean and efficient combustion process. This article aims at elucidating the effect of piston geometry on the engine performance and emissions of a metal DFI engine. Three different types of pistons were investigated and the main piston design features including the piston bowl diameter, piston bowl slope angle, duct angle and the injection nozzle position were examined. To achieve the target, computational fluid dynamics (CFD) simulations were conducted coupled to a reduced chemical kinetics mechanism. Extensive validations were performed against the measured data from a conventional diesel engine. To calibrate the soot model, genetic algorithm and machine learning methods were utilized. The simulation results highlight the pivotal role played by piston bowl diameter and fuel injection angle in controlling soot emissions of a DFI engine.

Commercial vehicle powertrain is called to respect a challenging roadmap for CO2 emissions reduction, quite complex to achieve just improving technologies currently on the market. In this perspective alternative solutions are gaining interest, and the use of green H2 as fuel for ICE is considered a high potential solution with fast and easy adoption. NOx emission is still a problem for H2 ICE and can be managed operating the engine with lean air fuel ratio all over the engine map. This combustion strategy will challenge the boosting system as lean H2 combustion will require quite higher air flow compared to diesel for the same power density in steady state. Similar problem will show up in transient response particularly when acceleration starts from low load and the exhaust gases enthalpy is very poor and insufficient to spin the turbine. The analysis presented in this paper will show and quantify the positive impact that a supercharger has on both the above mentions problems.

Heavy duty truck engines are quite difficult to electrify, due to the large amount of energy required on-board, in order to achieve a range comparable to that of diesels. This paper considers a commercial 6-cylinder engine with a displacement of 12.8 L, developed in two different versions. As a standard diesel, the engine is able to deliver more than 420 kW at 1800 rpm, whereas in the CNG configuration the maximum power output is 330 kW at 1800 rpm. Maintaining the same combustion chamber design of the last version, a theoretical study is carried out in order to run the engine on Hydrogen, compressed at 700 bar. The study is based on GT-Power simulations, adopting a predictive combustion model, calibrated with experimental results. The study shows that the implementation of a combustion system running on lean mixtures of Hydrogen, permits to cancel the emissions of CO2, while maintaining the same power output of the CNG engine.

This work aims at investigating the optimal configuration of an internal combustion engine fueled with bio-ethanol for improving its brake power and efficiency as well as for reducing the NOx emissions, in stationary applications. A turbocharged spark ignition engine characterized by a single-point injection was preliminarily considered; subsequently, a direct injection configuration was investigated. For both cases, a 1-D numerical model was developed to compare the injection configurations under stoichiometric conditions and different spark timings. The analysis shows that the direct injection guarantees: a limited improvement of brake power and efficiency when the same spark timing is adopted, while NOx emissions increases by 20%; an increase of 6% in brake power and 2 percentage points in brake thermal efficiency by adopting the knock limited spark advance, but an almost double NOx emissions increase.

The current work presents the results of an investigation on the impact of renewable fuels on the combustion and emissions of a turbocharged compression-ignition internal combustion engine. An experimental study was undertaken and the engine settings were not modified to account for the fuel's chemical and physical properties, to analyze the performance of the fuel as a potential drop-in alternative fuel. Three fuels were tested: mineral diesel, a blend of it with waste cooking oil biodiesel and a hydrogenated diesel. The analysis of the emissions at engine exhaust highlights that hydrogenated fuel allows to reduce CO, total hydrocarbon emissions, particulate matter and NOx.

Ammonia has emerged as a promising carbon-free alternative fuel for internal combustion engines (ICE), particularly in large-bore engine applications. However, integrating ammonia into conventional engines presents challenges, prompting the exploration of innovative combustion strategies like dual-fuel combustion. Nitrous oxide (N2O) emissions have emerged as a significant obstacle to the widespread adoption of ammonia in ICE. Various studies suggest that combining exhaust gas recirculation (EGR) with adjustments in inlet temperature and diesel injection timing can effectively mitigate nitrogen oxides (NOx) emissions across diverse operating conditions in dual-fuel diesel engines.

This study explores the feasibility of using a sustainable lignin-based fuel, consisting of 44 % lignin, 50 % ethanol, and 6 % water, in conventional compression ignition (CI) marine engines. Through experimental evaluations on a modified small-bore CI engine, we identified the primary challenges associated with lignin-based fuel, including engine startup and shutdown issues due to solvent evaporation and lignin solidification inside the fuel system, and deposit formation on cylinder walls leading to piston ring seizure. To address these issues, we developed a fuel switching system transitioning from lignin-based fuel to cleaning fuel with 85 vol% of acetone, 10 vol% of water and 5 vol% of ignition improving additive, effectively preventing system clogs.

The reduction of anthropogenic greenhouse gas emissions and ever stricter regulations on pollutant emissions in the transport sector require research and development of new, climate-friendly propulsion concepts. The use of renewable hydrogen as a fuel for internal combustion engines promises to provide a good solution especially for commercial vehicles. For optimum efficiency of the combustion process, hydrogen-specific engine components are required, which need to be tested on the test bench and analysed in simulation studies. This paper deals with the simulation-based investigation and optimisation of fuel injection in a 6-cylinder PFI commercial vehicle engine, which has been modified for hydrogen operation starting from a natural gas engine concept.

Though modal analysis is a common tool to evaluate the dynamic properties of a structure, there are still many individual decisions to be made during the process which are often based on experience and make it difficult for occasional users to gain reliable and correct results. One of those experience-based choices is the correct number and placement of reference points. This decision is especially important, because it must be made right in the beginning of the process and a wrong choice is only noticeable in the very end of the process. Picking the wrong reference points could result in incomplete modal analysis outcomes, as it might make certain modes undetectable, compounded by the user's lack of awareness about these missing modes. In the paper an innovative approach will be presented to choose the minimal number of mandatory reference points and their placement.

The engine acoustic character has always represented the product DNA, owing to its strong correlation with in-cylinder pressure gradient, components design and perceived quality. Best practice for engine acoustic characterization requires the employment of a hemi-anechoic chamber, a significant number of sensors and special acoustic insulation for engine ancillaries and transmission. This process is highly demanding in terms of cost and time due to multiple engine working points to be tested and consequent data post-processing. Since Neural Networks potentially predicting capabilities are apparently un-exploited in this research field, the following paper provides a tool able to acoustically estimate engine performance, processing system inputs (e.g. Injected Fuel, Rail Pressure) thanks to the employment of Multi Layer Perceptron (MLP, a feed forward Network working in stationary points).

The paper presents a theoretical framework for the detection and first-level preliminary identification of potential defects on aero-structure components while employing ultrasonic guided wave based structural health monitoring strategies, systems and tools. In particular, we focus our study on ground inspection using laser-Doppler scan of surface velocity field, which can also be partly reconstructed or monitored using point sensors and actuators on-board structurally integrated. Using direct wave field data, we first question the detectability of potential defects of unknown location, size, and detailed features. Defects could be manufacturing defects or variations, which may be acceptable from design and qualification standpoint; however, those may cause significant background signal artifacts in differentiating structure progressive damage or sudden failure like impact-induced damage and fracture.

Hypersonic flight vehicles have potential applications in strategic defence, space missions, and future civilian high-speed transportation systems. However, structural integration has significant challenges due to extreme aero-thermo-mechanical coupled effects. Scramjet-powered air-breathing hypersonic vehicles experience extreme heat loads induced by combustion, shock waves and viscous heat dissipation. An active cooling thermal protection system for scramjet applications has the highest potential for thermal load management, especially for long-duration flights, considering the weight penalty associated with the heavier passive thermal insulation structures. We consider the case of active cooling of scramjet engine structural walls with endothermic hydrocarbon fuel. We have developed a semi-analytical quasi-2D heat transfer model considering a prismatic core single cooling channel segment as a representative volume element (RVE) to analyse larger-scale problems.

The evaluation of aircraft characteristics through flight test maneuvers is fundamental to aviation safety and understanding flight attributes. This research project proposes a comprehensive methodology to detect and analyze aircraft maneuvers using full flight data, combining signal processing and machine learning techniques. Leveraging the Wavelet Transform, we unveil intricate temporal details within flight data, uncovering critical time-frequency insights essential for aviation safety. The integration of Long Short-Term Memory (LSTM) models enhances our ability to capture temporal dependencies, surpassing the capabilities of machine learning in isolation. These extracted maneuvers not only aid in safety but also find practical applications in system identification, air-data calibration, and performance analysis, significantly reducing pre-processing time for analysts.

Testing of ducted fuel injection (DFI) in a single-cylinder engine with production-like hardware previously showed that adding a duct structure increased soot emissions at the full load, rated speed operating point [1]. The authors hypothesized that the DFI flame, which travels faster than a conventional diesel combustion (CDC) flame, and has a shorter distance to travel, was being re-entrained into the on-going fuel injection around the lift-off length (LOL), thus reducing air entrainment into the on-going injection. The engine operating condition and the engine combustion chamber geometry were duplicated in a constant pressure vessel. The experimental setup used a 3D piston section combined with a glass fire deck allowing for a comparison between a CDC flame and a DFI flame via high-speed imaging. CH* imaging of the 3D piston profile view clearly confirmed the re-entrainment hypothesis presented in the previous engine work.