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Active prechamber combustion systems for SI engines represent a feasible and effective solution in reducing fuel consumption and pollutant emissions for both marine and ground heavy-duty engines. However, reliable and low-cost numerical approaches need to be developed to support and speed-up their industrial design considering their geometry complexity and the involved multiple flow length scales. This work presents a CFD methodology based on the RANS approach for the simulation of active prechamber spark-ignition engines. To reduce the computational time, the gas exchange process is computed only in the prechamber region to correctly describe the flow and mixture distributions, while the whole cylinder geometry is considered only for the power-cycle (compression, combustion and expansion). Outside the prechamber the in-cylinder flow field at IVC is estimated from the measured swirl ratio.

An advanced catalytic exhaust after-treatment system addresses the problem of NOX emissions from heavy-duty diesel trucks, relying on real-time catalyst modelling. The system consists of de-NOX catalysts, a device for injection of a reducing agent (diesel fuel) upstream the catalysts, and computer programmes to control the injection of the reducing agent and to model the engine and catalysts in real time. Experiments with 5 different air-assisted injectors were performed to determine the effect of injector design on the distribution of the injected diesel in the exhaust gas stream. A two-injector set-up was investigated to determine whether system efficiency could be increased without increasing the amount of catalyst or the amount of reducing agent necessary for the desired outcome. The results were verified by performing European standard transient cycle tests as well as stationary tests.

Growing awareness about CO2 emissions and their environmental implications are leading to an increase in the importance of thermal efficiency as criteria to design internal combustion engines (ICE). Heat transfer to the combustion chamber walls contributes to a decrease in the indicated efficiency. A strategy explored in this study to mitigate this efficiency loss is to promote low swirl conditions in the combustion chamber by using low swirl ratios. A decrease in swirl ratio leads to a reduction in heat transfer, but unfortunately, it can also lead to worsening of combustion development and a decrease in the gross indicated efficiency. Moreover, pumping work plays also an important role due to the effect of reduced intake restriction to generate the swirl motion. Current research evaluates the effect of a dedicated injection strategy to enhance combustion process when low swirl is used.

Thermal runaway is a critical safety concern in lithium-ion battery systems, emphasising the necessity to comprehend its behaviour in various modular setups. This research compares thermal runaway propagation in different modular configurations of lithium-ion batteries by analysing parameters such as cell spacing and applying phase change materials (PCMs) and Silica Aerogel. The study at the module level includes experimental validation and employs a comprehensive model considering heat transfer due to thermal runaway phenomena. It aims to identify the most effective modular configuration for mitigating thermal runaway risks and enhancing battery safety. The findings provide valuable insights into the design and operation of modular lithium-ion battery systems, guiding engineers and researchers in implementing best practices to improve safety and performance across various applications.

In the truck industry there is a continuous demand to increase the efficiency and to decrease the emissions. To acknowledge both these issues a waste heat recovery system (WHR) is combined with a partially premixed combustion (PPC) engine to deliver an efficient engine system. Over the past decades numerous attempts to increase the thermal efficiency of the diesel engine has been made. One such attempt is the PPC concept that has demonstrated potential for substantially increased thermal efficiency combined with much reduced emission levels. So far most work on increasing engine efficiency has been focused on improving the thermal efficiency of the engine while WHR, which has an excellent potential for another 1-5 % fuel consumption reduction, has not been researched that much yet. In this paper a WHR system using a Rankine cycle has been developed in a modeling environment using IPSEpro.

To advance vehicle lightweighting, chopped carbon fiber sheet molding compound (SMC) is identified as a promising material to replace metals. However, there are no effective tools and methods to predict the mechanical property of the chopped carbon fiber SMC due to the high complexity in microstructure features and the anisotropic properties. In this paper, a Representative Volume Element (RVE) approach is used to model the SMC microstructure. Two modeling methods, the Voronoi diagram-based method and the chip packing method, are developed to populate the RVE. The elastic moduli of the RVE are calculated and the two methods are compared with experimental tensile test conduct using Digital Image Correlation (DIC). Furthermore, the advantages and shortcomings of these two methods are discussed in terms of the required input information and the convenience of use in the integrated processing-microstructure-property analysis.

The purpose of present numerical study was to extend the operating range of alcohol (methanol and ethanol) fueled Homogeneous Charge Compression Ignition (HCCI) engine under low load conditions. Ignition of pure methanol and ethanol under HCCI mode of operation requires high intake temperatures and misfires at low loads are common in HCCI engines. Three methods have been adapted to optimize the use of methanol and ethanol for HCCI operation without increasing the intake temperature. First, blending methanol and ethanol with ignition improver, namely di-methyl ether (DME) and di-ethyl ether (DEE), was used to increase the cetane number and ignitability of premixed charge. Second, based on the blended fuels, the spark assistance was used to reduce required intake temperature for auto-ignition. Third, DME and DEE were directly injected to methanol and ethanol operated HCCI engine, in the form of Reactivity Controlled Compression Ignition (RCCI) combustion.

Emissions and in-cylinder pressure traces are used to compare the relative importance of soot formation and soot oxidation in a heavy-duty diesel engine. The equivalence ratio at the lift-off length is estimated with an empirical correlation and an idealized model of diesel spray. No correlation is found between the equivalence ratio at lift-off and the soot emissions. This confirms that trends in soot emissions cannot be directly understood by the soot formation process. The coupling between soot emission levels and late heat release after end of injection is also studied. A regression model describing soot emissions as function of global engine parameters influencing soot oxidation is proposed. Overall, the results of this analysis indicate that soot emissions can be understood in terms of the efficiency of the oxidation process.

The present work describes the numerical modeling of medium-speed marine engines, operating in a fumigated dual-fuel mode, i.e. with the second fuel injected in the ports. This engine technology allows reducing engine-out emissions while maintaining the engine efficiency and can be fairly easily retrofitted from current diesel engines. The main premixed fuel that is added can be a low-carbon one and can additionally be of a renewable nature, thereby reducing or even completely removing the global warming impact. To fully optimize the operational parameters of such a large marine engine, computational fluid dynamics can be very helpful. Accurately describing the combustion process in such an engine is key, as the prediction of the heat release and the pollutant formation is crucial. Auto-ignition of the diesel fuel needs to be captured, followed by the combustion and flame propagation of the premixed fuel.

Increased research is being driven by the automotive industry facing challenges, requiring to comply with both current and future emissions legislation, and to lower the fuel consumption. The reason for this legislation is to restrict the harmful pollution which every year causes 3.3 million premature deaths worldwide [1]. One factor that causes this pollution is NOx emissions. NOx emission legislation has been reduced from 8 g/kWh (Euro I) down to 0.4 g/kWh (Euro VI) and recently new legislation for ammonia slip which increase the challenge of exhaust aftertreatment with a SCR system. In order to achieve a good NOx conversion together with a low slip of ammonia, small droplets of Urea solution needs to be injected which can be rapidly evaporated and mixed into the flow of exhaust gases.

In the automotive industry, the piezo-based in-cylinder pressure sensor is getting commercialized and used in production vehicles. For example, the pressure sensor offers the opportunity to design algorithms for estimation of engine emissions, such as soot and NO , during a combustion cycle. In this paper a zero-dimensional NO model for a diesel engine is implemented that will be used in real time. The model is based on the thermal NO formation and the Zeldovich mechanism using two non-geometrical zones: burned and unburned zone. The influence of EGR on combustion temperature was modeled using a well-known thermodynamic identity where specific heat at constant pressure is included. Specific heat will vary with temperature and the gas composition. The model was implemented in LabVIEW using tools specific for an FPGA (Field-Programmable Gate Array).

SI engines fueled with hydrogen represent a promising powertrain solution to meet the ambitious target of carbon-free emissions at the tailpipe. Therefore, fast and reliable numerical tools can significantly support the automotive industry in the optimization of such technology. In this work, a 1D-3D methodology is presented to simulate in detail the combustion process with minimal computational effort. First, a 1D analysis of the complete engine cycle is carried out on the user-defined powertrain configuration. The purpose is to achieve reliable boundary conditions for the combustion chamber, based on realistic engine parameters. Then, a 3D simulation of the power-cycle is performed to mimic the combustion process. The flow velocity and turbulence distributions are initialized without the need of simulating the gas exchange process, according to a validated technique.

The combustion of dual-fuel engines usually uses a pilot flame to burn out a background fuel inside a cylinder under high compression. The background fuel can be either a gaseous fuel or a volatile liquid fuel, commonly with low reactivity to prevent premature combustion and engine knocking; whereas the pilot flame is normally set off with the direct injection of a liquid fuel with adequate reactivity that is suitable for deterministic auto-ignition with a high compression ratio. In this work, directly injected butanol is used to generate the pilot flame, while intake port injected ethanol or butanol is employed as the background fuel. Compared with the conventional diesel-only combustion, dual-fuel operations not only broaden the fuel applicability, but also enhance the potential for clean combustion, in high efficiency engines. The amount of background fuel and the scheduling of pilot flame are investigated through extensive laboratory experiments.

In recent years, with the increase of traffic accidents and traffic jams, lane change, as one of the most important and commonly automatic driving operations for autonomous vehicles, is receiving attention in academia. It is considered to be one of the important solutions that play an important role in improving road traffic safety and efficiency. However, most existing lane-changing models are rule-based lane-changing models. These models only assume a one-direction impact of surrounding vehicles on the lane-changing vehicle. In fact, lane change is a process of mutual interaction between vehicles due to the complexity and uncertainty of the traffic environment. Moreover, the safety and efficiency of existing lane-changing decision algorithms need to be improved. In this paper, we proposed a multivehicle cooperative control approach with a distributed control structure to control the model.

Percussive riveting is a widely used way of fastening in the field of aircraft assembly, which used to be done manually. Nowadays, replacing the traditional percussive riveting with automated percussive riveting becomes a trend worldwide, which improves the quality of riveting significantly. For the automated riveting system used in aircraft assembly, reliability is of great importance, deserving to be deeply researched and fully enhanced. In this paper, a high reliable automated percussive riveting system integrated into a dual robot drilling and riveting system is proposed. The riveting system consists of the hammer part and the bucking bar part. And both parts have been optimized to enhance the reliability. In the hammer side, proximity switches are fully used to detect the state of rivet insertion.

Ammonia has attracted the attention of a growing number of researchers in recent years. However, some properties of ammonia (e.g., low laminar burning velocity, high ignition energy, etc.) inhibit its direct application in engines. Several routes have been proposed to overcome these problems, such as oxygen enrichment, partial fuel cracking strategy and co-combustion with more reactive fuels. Improving the reactivity of ammonia from the oxidizer side is also practical. Ozone is a highly reactive oxidizer which can be easily and rapidly generated through electrical plasma and is an effective promoter applicable for a variety of fuels. The dissociation reaction of ozone increases the concentration of reactive radicals and promotes chain-propagating reactions. Thus, obtaining accurate rate constants of reactions related to ozone is necessary, especially at elevated to high pressure range which is closer to engine-relevant conditions.

As the number of actuators and sensors increases in modern combustion engines, the task of optimizing engine performance becomes increasingly complex. Efficient information processing techniques are therefore important, both for off-line calibration of engine maps, and on-line adjustments based on sensor data. In-cylinder pressure sensors are slowly spreading from laboratory use to production engines, thus making data with high temporal resolution of the combustion process available. The standard way of using the cylinder pressure data for control and diagnostics is to focus on a few important physical features extracted from the pressure trace, such as the combustion phasing CA50, the indicated mean effective pressure IMEP, and the ignition delay. These features give important information on the combustion process, but much information is lost as the information from the high-resolution pressure trace is condensed into a few key parameters.

The prediction of agents' future trajectory is a crucial task in supporting advanced driver-assistance systems (ADAS) and plays a vital role in ensuring safe decisions for autonomous driving (AD). Currently, prevailing trajectory prediction methods heavily rely on high-definition maps (HD maps) as a source of prior knowledge. While HD maps enhance the accuracy of trajectory prediction by providing information about the surrounding environment, their widespread use is limited due to their high cost and legal restrictions. Furthermore, due to object occlusion, limited field of view, and other factors, the historical trajectory of the target agent is often incomplete This limitation significantly reduces the accuracy of trajectory prediction. Therefore, this paper proposes ETSA-Pred, a mapless trajectory prediction model that incorporates enhanced temporal modeling and spatial self-attention.

The combustion timing in internal combustion engines affects the fuel consumption, in-cylinder peak pressure, engine noise and emission levels. The combination of an in-cylinder pressure sensor together with a direct injection fuel system lends itself well for cycle-to-cycle control of the combustion timing. This paper presents a method of controlling the combustion timing by the use of a cycle-to-cycle injection-timing algorithm. At each cycle the currently estimated heat-release rate is used to predict the in-cylinder pressure change due to a combustion-timing shift. The prediction is then used to obtain a cycle-to-cycle model that relates combustion timing to gross indicated mean effective pressure, max pressure and max pressure derivative. Then the injection timing that controls the combustion timing is decided by solving an optimization problem involving the model obtained.

Fuel film deposits on combustion chamber walls are understood to be the main source of particle emissions in GDI engines under homogenous charge operation. More precisely, the liquid film that remains on the injector tip after the end of injection is a fuel rich zone that undergoes pyrolysis reactions leading to the formation of poly-aromatic hydrocarbons (PAH) known to be the precursors of soot. The physical phenomena accompanying the fuel film deposit, evaporation, and the chemical reactions associated to the injector film are not yet fully understood and require high fidelity CFD simulations and controlled experimental campaigns in optically accessible engines. To this end, a simplified model based on physical principles is developed in this work, which couples an analytical model for liquid film formation and evaporation on the injector tip with a stochastic particle dynamics model for particle formation.