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In pursuing sustainable automotive technologies, exploring alternative fuels for hybrid vehicles is crucial in reducing environmental impact and aligning with global carbon emission reduction goals. This work compares methanol and naphtha as potential suitable alternative fuels for running in a battery-driven light-duty hybrid vehicle by comparing their performance with the diesel baseline engine. This work employs a 0-D vehicle simulation model within the GT-Power suite to replicate vehicle dynamics under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC). The vehicle choice enables the assessment of a delivery application scenario using distinct payload capacities: 0%, 25%, 50%, and 100%. The model is fed with engine maps derived from previous experimental work conducted in the same engine, in which a full calibration was obtained that ensures the engine's operability in a wide region of rotational speed and loads.

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.

Predicting and preventing combustion anomalies leads to safe and efficient operation of the hydrogen internal combustion engine. This research presents the application of three machine learning (ML) models – K-Nearest Neighbors (KNN), Random Forest (RF) and Logistic Regression (LR) – for the prediction of combustion anomalies in a hydrogen internal combustion engine. A small experimental dataset was used to train the models and posterior experiments were used to evaluate their performance and predicting capabilities (both in operating points -speed and load- within the training dataset and operating points in other areas of the engine map). KNN and RF exhibit superior accuracy in classifying combustion anomalies in the training and testing data, particularly in minimizing false negatives, which could have detrimental effects on the engine.

Using renewable fuels is a reliable approach for decarbonization of combustion engines. iso-Butanol and n-butanol are known as longer chain alcohols and have the potential of being used as gasoline substitute or a renewable fraction of gasoline. The combustion behavior of renewable fuels in modern combustion engines and advanced combustion concepts is not well understood yet. Low-temperature combustion (LTC) is a concept that is a basis for some of the low emissions-high efficiency combustion technologies. Fuel ɸ-sensitivity is known as a key factor to be considered for tailoring fuels for these engines. The Lund ɸ-sensitivity method is an empirical test method for evaluation of the ɸ-sensitivity of liquid fuels and evaluate fuel behavior in thermal. iso-Butanol and n-butanol are two alcohols which like other alcohol exhibit nonlinear behavior when blended with (surrogate) gasoline in terms of RON and MON.

Methanol is currently being evaluated as a promising alternative fuel for internal combustion engines, due to being attainable by carbon neutral or negative pathways (renewable energy and carbon capture technology). The low ignitability of methanol has made it attractive mostly as a fuel for spark ignition engines, however the low sooting properties of the fuel could potentially reduce the NOx-soot tradeoff present in compression ignition engines. In this work, using a 4-cylinder engine with compression ratio modified from 16:1 to 19:1, methanol combustion is evaluated under five operating conditions in terms of fuel consumption, criteria pollutants, CO2 emissions and engine efficiency in addition to the qualitative assessment of the combustion stability. It was found that combustion is stable at medium to high loads, with medium load NOx emissions levels at least 30% lower than the original diesel engine and comparable emissions at maximum load conditions.

In several regions, such as Europe, California, among others, the switch to Electric Vehicles (EVs) has been heavily pushed by policymakers for their high powertrain efficiency and zero tailpipe emissions compared to conventional Internal Combustion Engine Vehicles (ICEVs). Consequently, only zero tailpipe emission vehicles will be sold in Europe from 2035 for the passenger cars and vans segment. But an EV does emit CO2 emissions across its life cycle, mainly during production, and the Well-to-Tank (WTT) phase, i.e., from the electricity generation used to charge the batteries. Nonetheless, due to the high efficiency of the electric powertrain, the energy consumption is significantly less, making the cost of operation significantly low for EVs. Thus, clean electricity grid and cheap energy costs can make EVs one of the best options for decarbonizing transportation systems.

De-fossilization is an increasingly important trend in the energy sector. In the transport sector the de-fossilization efforts have been centered in promoting the electrification of vehicles, nonetheless other pathways, like the use of carbon neutral or carbon-offsetting fuels under current vehicle fleets, are also worth considering. Low-carbon fuels (LCF) can be synthetized from sources that can take advantage of the carbon already present in the atmosphere (either by technologies like direct carbon capture or biological processes like photosynthesis in biofuels) and use energy from renewable sources for the necessary industrial processes. Although, LCFs can be compared to fossil fuels as energy sources for internal combustion engines, their composition is not the same and their properties can modify the engine combustion and emissions.

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.

Fleet electrification has been demonstrated as a feasible solution to decarbonize the heavy-duty transportation sector. The combination of hybridization and advanced combustion concepts may provide further advantages by also introducing reductions on criteria pollutants such as nitrogen oxides and soot. In this scenario, the interplay among the different energy paths must be understood and quantified to extract the full potential of the powertrain. One of the key devices in such powertrains is the battery, which involves different aspects regarding operation, safety, and degradation. Despite this complexity, most of the models still rely on resistance-capacity models to describe the battery operation. These models may lead to unpractical results since the current flow is governed by limiters rather than physical laws. Additionally, phenomena related with battery degradation, which decreases the nominal capacity and enhances the heat generation are also not considered in this approach.

In the challenge to reduce CO2, NOx and PM emissions, the application of natural gas or biogas in engines is a viable approach. In heavy duty and marine, either a conventional dual fuel (CDF), or a reactivity-controlled compression ignition (RCCI) approach is feasible on existing diesel engines. In both technologies a pilot diesel injection is used to ignite the premixed natural gas. However, the influence of injection-timing and -pressure on the start of combustion timing (SOC) is opposite between both modes. For a single operating point these relations can be explained by a detailed CFD simulation, but an intuitive overall explanation is lacking. This makes it difficult to incorporate both modes into one engine application, using a single controller. In an experimental campaign by the authors, on a medium speed engine, the lowest emissions were found to be very close to the SOC corresponding to the transition from RCCI to CDF.

Emissions regulations for engine and vehicle manufacturers are bound to become more limiting to prevent greenhouse gas emissions and mitigate the negative effects that potentiate global warming. To fulfill the energy demand necessary in the transportation sector for the short-to-medium term, a parallel optimization of the internal combustion engine, powertrain and fuels is necessary. The combination of novel combustion modes like the reactivity-controlled compression ignition (RCCI), that seeks the benefits of both compression ignition and spark ignition engines, with the so-called e-fuels, that reduce the carbon footprint from well-to-wheel, is worth exploring. This work investigates the potential of the RCCI concept using OMEx-gasoline to reduce the engine-out emissions beyond the current EURO VI legislation. To do so, eight representative operating conditions from several driving cycles for heavy-duty vehicles will be explored experimentally.

Advanced combustion concepts such as reactivity controlled compression ignition (RCCI) have been proven to be capable of fundamentally improve the conventional Diesel combustion by mitigating or avoiding the soot-NOx trade-off, while delivering comparable or better thermal efficiency. To further facilitate the development of the RCCI technology, a robust and possibly computationally efficient simulation framework is needed. While many successful studies have been published using 3D-CFD coupled with detailed combustion chemistry solvers, the maturity level of the 0D/1D based software solution offerings is relatively limited. The close interaction between physical and chemical processes challenges the development of predictive numerical tools, particularly when spatial information is not available.

Dual-mode dual-fuel combustion is a promising combustion concept to achieve the required emissions and CO2 reductions imposed by the next standards. Nonetheless, the fuel formulation requirements are stricter than for the single-fuel combustion concepts as the combustion concept relies on the reactivity of two different fuels. This work investigates the effect of the low reactivity fuel sensitivity (S=RON-MON) and the octane number at different operating conditions representative of the different combustion regimes found during the dual-mode dual-fuel operation. For this purpose, experimental tests were performed using a PRF 95 with three different sensitivities (S0, S5 and S10) at operating conditions of 25% load/950 rpm, 50%/1800 rpm and 100%/2200 rpm. Moreover, air sweeps varying ±10% around a reference air mass were performed at 25%/1800 rpm and 50%/1800 rpm. Conventional diesel fuel was used as high reactivity fuel in all the cases.

Compression ignition engines are widely used for transport and energy generation due to their high efficiency and low fuel consumption. To minimize the environmental impact of this technology, the pollutant emissions levels at the exhaust are strictly regulated. To reduce the after-treatment needs, alternative strategies as the low temperature combustion (LTC) concepts are being investigated recently. The reactivity controlled compression ignition (RCCI) uses two fuels (direct- and port- injected) with different reactivity to control the in-cylinder mixture reactivity by adjusting the proportion of both fuels. In spite of the proportion of the port-injected fuel is typically higher than the direct-injected one, the characteristics of the latter play a main role on the combustion process. Use of gasoline for direct injection is attractive to retard the start of combustion and to improve the air-fuel mixing process.

The increasingly stringent emissions regulations together with the demand of highly efficient vehicles from the customers, lead to rapid developments of distinct powertrain solutions, especially when the electrification is present in a certain degree. The combination of electric machines with conventional powertrains diversifies the powertrain architectures and brings the opportunity to save energy in greater extents. On the other hand, alternative combustion modes as reactivity controlled compression ignition (RCCI) have shown to provide simultaneous ultra-low NOx and soot emissions with similar or better thermal efficiency than conventional diesel combustion (CDC). In addition, it is necessary to introduce more renewable fuels as ethanol to reduce the total CO2 emitted to the atmosphere, also called well-to-wheel (WTW) emission, in the transport sector.

With demanding emissions legislations and the need for higher efficiency, new technologies for compression ignition engines are in development. One of them relies on reducing the heat losses of the engine during the combustion process as well as to devise injection strategies that reduce soot formation. Therefore, it is necessary a better comprehension about the turbulent kinetic energy (TKE) distribution inside the cylinder and how it is affected by the interaction between air flow motion and fuel spray. Furthermore, new diesel engines are characterized by massive decrease of NOx emissions. Therefore, considering the well-known NOx-soot trade-off, it is necessary a better comprehension and overall quantification of soot formation and how the different injection strategies can impact it.

It is known that in-cylinder airflow structures during intake and compression strokes deeply affects the combustion process in compression ignition (CI) engines. This work presents a methodology for the analysis of the swirling structures by means of the CFD proprietary code Converge 2.3. The methodology is based on the CFD modelling and the comparison of results with in-cylinder velocity fields measured by particle image velocimetry (PIV). Furthermore, the analysis is extended to the accuracy evaluation of other methods available to define the flow in the cylinder of internal combustion engines, such as experiments in steady flow rigs. These methods, in junction with simple phenomenological models, have been traditionally used to determine some of the fundamental variables that define the in-cylinder flow in ICE engines. The CFD analysis is focused in the flow structures around top dead centre (TDC) at the end of the compression stroke.

Reactivity controlled compression ignition (RCCI) combustion has demonstrated to be able to avoid the NOx-soot trade-off appearing during conventional diesel combustion (CDC), with similar or better thermal efficiency than CDC under a wide variety of engine platforms. However, a major challenge of this concept comes from the high hydrocarbon (HC) and carbon monoxide (CO) emission levels, which are orders of magnitude higher than CDC and similar to those of port fuel injected (PFI) gasoline engines. The higher HC and CO emissions combined with the lower exhaust temperatures during RCCI operation present a challenge for current exhaust aftertreatment technologies. RCCI has been successfully implemented on different compression ignition engine platforms with only minor modifications on the combustion system to include a PFI for feeding the engine with the low reactivity fuel.

The Engine Combustion Network (ECN) is a coordinate effort from research partners from all over the world which aims at creating a large experimental database to validate CFD calculations. Two injectors from ECN, namely Spray C and D, have been compared in a constant pressure flow vessel, which enables a field of view of more than 100 mm. Both nozzles have been designed with similar flow metrics, with Spray D having a convergent hole shape and Spray C a cylindrical one, the latter being therefore more prone to cavitation. Although the focus of the study is on reacting conditions, some inert cases have also been measured. High speed schlieren imaging, OH* chemiluminescence visualization and head-on broadband luminosity have been used as combustion diagnostics to evaluate ignition delay, lift off length and reacting tip penetration. Parametric variations include ambient temperature, oxygen content and injection pressure variations.

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.