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With ever-demanding emission legislations in Compression Ignition (CI) engines, new premixed combustion strategies have been developed in recent years seeking both, emissions and performance improvements. Since it has been shown that in-cylinder air flow affects the combustion process, and hence the overall engine performance, the study of swirling structures and its interaction with fuel injection are of great interest. In this regard, possible Turbulent Kinetic Energy (TKE) distribution changes after fuel injection may be a key parameter for achieving performance improvements by reducing in-cylinder heat transfer. Consequently, this paper aims to gain an insight into spray-swirl interaction through the analysis of in-cylinder velocity fields measured by Particle Image Velocimetry (PIV) when PCCI conditions are proposed. Experiments are carried out in a single cylinder optical Diesel engine with bowl-in-piston geometry.

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.

Gas engines (fuelled with CNG, LNG or Biogas) for generation of power and heat are, to this date, taking up larger shares of the market with respect to diesel engines. In order to meet the limit imposed by the TA-Luft regulations on stationary engines, lean combustion represents a viable solution for achieving lower emissions as well as efficiency levels comparable with diesel engines. Leaner mixtures however affect the combustion stability as the flame propagation velocity and consequently heat release rate are slowed down. As a strategy to deliver higher ignition energy, an active pre-chamber may be used. This work focuses on assessing the performance of a pre-chamber combustion configuration in a stationary heavy-duty engine for power generation, operating at different loads, air-to-fuel ratios and spark timings.

The influence of pressure and temperature on some of the important thermodynamic properties of diesel fuels has been assessed for a set of fuels. The study focuses on the experimental determination of the speed of sound, density and compressibility (via the bulk modulus) of these fuels by means of a method that is thoroughly described in this paper. The setup makes use of a common-rail injection system in order to transmit a pressure wave through a high-pressure line and measure the time it takes for the wave to travel a given distance. Measurements have been performed in a wide range of pressures (from atmospheric pressure up to 200 MPa) and temperatures (from 303 to 353 K), in order to generate a fuel properties database for modelers on the field of injection systems for diesel engines to incorporate to their simulations.

Ever decreasing permitted emission levels and the necessity of more efficient engines demand a better understanding of in-cylinder phenomena. In swirl-supported compression ignition (CI) engines, mean in-cylinder flow structures formed during the intake stroke deeply influence mixture preparation prior to combustion, heat transfer and pollutant oxidation all of which could potentially improve engine performance. Therefore, the ability to characterize these mean flow structures is relevant for achieving performance improvements. CI mean flow structure is mainly described by a precessing vortex. The location of the vortex center is key for the characterization of the flow structure. Consequently, this work aims at evaluating algorithms that allow for the location of the vortex center both, in ensemble-averaged velocity fields and in instantaneous velocity fields.

Engine Combustion Network promotes fundamental investigations on a number of different spray configurations with the goal of providing experimental results under highly controlled conditions for CFD validation. Most of the available experiments up to now have been obtained in spray vessels, which miss some of the interactions governing spray evolution in the combustion chamber of an engine, such as the jet wall interaction and the transient conditions in the combustion chamber. The main aim of the present research is to compare the results obtained with a three-hole, 90 μm injector, known as ECN’s Spray B, in these constant-volume vessels and more recent Heavy-Duty engines with those obtained in a Light Duty Single Cylinder Optical Engine, under inert and reactive conditions, using n-dodecane. In-cylinder conditions during the injection were estimated by means of a 1-D and 0-D model simulation, accounting for heat transfer and in-cylinder mass evolution.

Focusing on the dual-mode dual-fuel (DMDF) combustion concept, a combined optimization of the piston bowl geometry with the fuel injection strategy was conducted at low, mid, and high loads. By coupling the KIVA-3V code with the enhanced genetic algorithm (GA), a total of 14 parameters including the piston bowl geometric parameters and the injection parameters were optimized with the objective of meeting Euro VI regulations while improving the fuel efficiency. The optimal piston bowl shape coupled with the corresponding injection strategy was summarized and integrated at various loads. Furthermore, the effects of the key geometric parameters were investigated in terms of organizing the in-cylinder flow, influencing the energy distribution, and affecting the emissions. The results indicate that the behavior of the DMDF combustion mode is further enhanced in the aspects of improving the fuel economy and controlling the emissions after the bowl geometry optimization.

Electrification and hybridization of powerplants in the transportation sector is one of the most important changes in the last few decades. Lithium-ion batteries are the main energy storage systems, but despite the maturity of this technology, it has certain constrains compared to traditional internal combustion engines in the day-to-day usage. As the operating conditions of the batteries are pushed to the limits to overcome certain disadvantages relative to other conventional systems like charge and discharge times or vehicle driving range, new concerns and safety limitations must be considered. High power rates and cooling deficiencies can produce excessive operating temperatures within the cells, leading to problems with degradation or even unchain chemical reactions that can end in thermal runaway, one of the most worrying failure modes attaining electric platforms nowadays.

The combination of more strict regulation for pollutant and CO2 emissions and the new testing cycles, covering a wider range of transient conditions, makes very interesting the development of predictive tools for engine design and pre-calibration. This paper describes a new integrated Virtual Engine Model (VEMOD) that has been developed as a standalone tool to simulate new standard testing cycles. The VEMOD is based on a wave-action model that carries out the thermo-and fluid dynamics calculation of the gas in each part of the engine. In the model, the engine is represented by means of 1D ducts, while the volumes, such as cylinders and reservoirs, are considered as 0D elements. Different sub-models are included in the VEMOD to take into account all the relevant phenomena. Thus, the combustion process is calculated by the Apparent Combustion Time (ACT) 1D model, responsible for the prediction of the rate of heat release and NOx formation.

In recent years, the automotive industry has been increasingly committed to developing new solutions for better and more efficient engines. One of them is the use of new insulating materials (thermal conductivity < 0.4 W/m-K, heat capacitance < 500 kJ/m3-K) to coat the engine combustion chamber walls, as well as the exhaust manifold. The main idea when coating the combustion chamber with these materials is to obtain a reduction of the temperature difference (thermal swing) between gas and walls during the engine cycle and minimize heat losses. Experimental measurements of the possible performance improvements are very difficult to obtain, mainly because the techniques available to measure wall temperature are limited. Therefore, simulations are typically used to investigate insulated combustion chambers. Nevertheless, the new generation of insulating coatings is posing challenges to numerical modelling, as layer thickness is very small (~100 μm).

A genetic algorithm (GA) optimization methodology is applied to the design of the combustion system of a heavy-duty (HD) Diesel engine fueled with dimethyl ether (DME). The study has two objectives, the optimization of a conventional diffusion-controlled combustion system aiming to achieve US2010 targets and the optimization of a stoichiometric combustion system coupled with a three way catalyst (TWC) to further control NOx emissions and achieve US2030 emission standards. These optimizations include the key combustion system related hardware, bowl geometry and injection nozzle design as input factors, together with the most relevant air management and injection settings. The GA was linked to the KIVA CFD code and an automated grid generation tool to perform a single-objective optimization. The target of the optimizations is to improve net indicated efficiency (NIE) while keeping NOx emissions, peak pressure and pressure rise rate under their corresponding target levels.

Accelerating rate calorimetry (ARC) has emerged as a powerful tool for evaluating the thermal behavior of Li-ion cells and identifying potential safety hazards. In this work, a new physical thermal model has been developed based on the first law of thermodynamics for analyzing heat and mass generated by Lithium-ion battery cells under thermal abuse conditions during EV-ARC tests. The analysis is based on the experimental data gathered from an ARC, including different temperatures and pressure inside a gas-tight canister located in the calorimeter chamber, as well as the gas composition at the end of the test. The energy balance of the battery cell includes: the energy released by the cell, the internal energy of the elements inside the canister, heat transfer between elements inside the canister, as well as the mass transfer between the cell and the gases inside the canister.

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 distribution, application of phase change materials (PCMs), and implementing insulating materials. The study at the module level includes experimental validation and employs a comprehensive model considering heat transfer due to electrical performance and 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.