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Methanol has recently emerged as a promising fuel for internal combustion engines due to its multiple carbon-neutral production routes and advantageous properties when combusting. Methanol is intrinsically more suitable for spark-ignition (SI) operation thanks to its high octane number, but its potential in heavy-duty applications also encourages engine manufacturers in this field to retrofit their existing compression-ignition products into methanol/diesel dual-fuel (DF) operation. For both SI operation and DF operation, injecting methanol into the engine’s intake path at low pressure is a relatively simple and robust method to introduce methanol into the cylinders. However, the much higher heat of vaporization (HoV) of methanol compared to conventional SI fuels like gasoline can be a double-edged sword.

To mitigate climate change, it is essential that sustainable technologies emerge in the transport industry. One viable solution is the use of methanol or hydrogen combined with internal combustion engines (ICEs). The dual-fuel technology in particular, in which a diesel pilot ignites port fuel injected methanol or hydrogen, is of great interest to transition from diesel engines to ICEs using purely these fuels. This approach allows for a significant portion of fossil diesel to be replaced with sustainable methanol or hydrogen, while maintaining high efficiencies and the possibility to run solely on diesel if required. Additionally, lower engine-out pollutant emissions (NOx, soot) are produced. Although multiple experimental research results are available, numerical literature on both fuels in dual-fuel mode is scarce. Therefore, this study aims to develop a multi-zone dual-fuel combustion model for engine simulations.

An increasing need to lower greenhouse gas emissions, and so move away from fossil fuels like diesel and gasoline, has greatly increased the interest for methanol. Methanol can be produced from renewable sources and eliminate soot emissions from combustion engines [1]. Since compression ignition (CI) engines are used for the majority of commercial applications, research is intensifying into the use of methanol, as a replacement for diesel fuel, in CI engines. This includes work on dual-fuel set-ups, different fuel blends with methanol, ignition enhancers mixed with methanol, and partially premixed combustion (PPC) strategies with methanol. However, methanol is difficult to ignite, using compression alone, at low load conditions. The problem comes from methanol’s high octane number, low lower heating value and high heat of vaporization, which add up to a lot of heat being needed from the start to combust methanol [2].

In order to reduce the carbon footprint of the Internal Combustion Engine (ICE), biofuels have been in use for a number of years. One of the problems with first-generation (1G) biofuels however is their competition with food production. In search of second-generation (2G) biofuels, that are not in competition with food agriculture, a novel biorefinery process has been developed to produce biofuel from woody biomass sources. This novel technique, part of the Belgian federal government funded Ad-Libio project, uses a catalytic process that operates at low temperature and is able to convert 2G feedstock into a stable light naphtha. The bulk of the yield consists out of hydrocarbons containing five to six carbon atoms, along with a fraction of oxygenates and aromatics. The oxygen content and the aromaticity of the hydrocarbons can be varied, both of which have a significant influence on the fuel’s combustion and emission characteristics when used in Internal Combustion Engines.

To speed up the development of the next-generation combustion engines with renewable fuels, the importance of reliable and robust simulations cannot be overemphasized. Compared to gasoline, methanol is a promising fuel for spark-ignited engines due to its higher research octane number to resist auto-ignition, higher flame speed for faster combustion and higher heat of vaporization for intake charge cooling. These advantageous properties all contribute to higher thermal efficiency and lower knock tendency, and they need to be well-captured in the simulation environment in order to generate accurate predictions. In this paper, the sub-models which estimate the burning velocities and ignition delay of methanol are revisited. These building blocks are implemented and integrated in a quasi-dimensional simulation environment to predict the combustion behavior, which are subsequently validated against test data measured on both light-duty and heavy-duty engines.

Methanol is a promising fuel for future spark-ignition engines. Its properties enable increased engine efficiency. Moreover, the ease with which methanol can be reformed, using waste exhaust heat, potentially offers a pathway to even higher efficiencies. The primary objective of this study was to build and validate a model for a methanol fueled direct-injection spark-ignition engine with on-board fuel reforming for future investigation and optimization. The second objective was to understand the combustion characteristics, energy losses and engine efficiency. The base engine model was developed and calibrated before adding a reformed-exhaust gas recirculation system (R-EGR). A newly developed laminar burning velocity correlation with universal dilution term was implemented into the model to predict the laminar burning velocity with the presence of hydrogen in the reforming products.

In this work, the possibility to perform a cold-flow simulation as a way to improve the accuracy of the starting conditions for a combustion simulation is examined. Specifically, a dual-fuel marine engine running on methanol/diesel and natural gas/diesel fueling conditions is investigated. Dual-fuel engines can provide a short-term solution to cope with the more stringent emission legislations in the maritime sector. Both natural gas and methanol appear to be interesting alternative fuels that can be used as main fuel in these dual-fuel engines. Nevertheless, it is observed that combustion problems occur at part load using these alternative fuels. Therefore, different methods to increase the combustion efficiency at part load are investigated. Numerical simulations prove to be very suitable hereto, as they are an efficient way to study the effect of different parameters on the combustion characteristics.

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.

Lean operation is a promising approach to increase the engine efficiency. One of the main challenges for lean-burn technology is the combustion instability. Using a high laminar burning velocity fuel such as methanol might solve that problem. The potential of lean-burn limit extension with methanol was investigated through a comparison with conventional gasoline. In this work, a direct injection turbocharged SI engine was operated at wide open throttle (WOT), with the load controlled by a lean-burn strategy. The amount of fuel was decreased (or lambda increased) until the combustion became unstable. For methanol, the lambda limit was about 1.5, higher than the lambda limit for gasoline which was only about 1.2. The brake thermal efficiency for methanol increased as lambda increased and reached its peak at ~41% in a lambda range of 1.2-1.4. Then, the efficiency decreased as lambda increased.

Low Temperature Combustion is a technology that enables achieving both a higher efficiency and simultaneously lower emissions of NOx and particulate matter. It is a noun for combustion regimes that operate with a lean air-fuel mixture and where the combustion occurs at a low temperature, such as Homogeneous Charge Compression Ignition and Partially Premixed Combustion. In this work a new model is proposed to predict the instantaneous heat flux in engines with Low Temperature Combustion. In-cylinder heat flux measurements were used to construct this model. The new model addresses two shortcomings of the existing heat transfer models already present during motored operation: the phasing of the instantaneous heat flux and the overprediction of the heat flux during the expansion phase. This was achieved by implementing the in-cylinder turbulence in the heat transfer model. The heat transfer during the combustion was taken into account by using the turbulence generated in the burned zone.

The present work details a study of the heat flux through the walls of an internal combustion engine. The determination of this heat flux is an important aspect in engine optimization, as it influences the power, efficiency and the emissions of the engine. Therefore, a set of simulation tools in the OpenFOAM® software has been developed, that allows the calculation of the heat transfer through engine walls for ICEs. Normal practice in these types of engine simulations is to apply a wall function model to calculate the heat flux, rather than resolving the complete thermo-viscous boundary layer, and perform simulations of the closed engine cycle. When dealing with a complex engine, this methodology will reduce the overall computational cost. It however increases the need to rely on assumptions on both the initial flow field and the behavior in the near-wall region.

Engine optimization requires a good understanding of the in-cylinder heat transfer since it affects the power output, engine efficiency and emissions of the engine. However little is known about the convective heat transfer inside the combustion chamber due to its complexity. To aid the understanding of the heat transfer phenomena in a Spark Ignition (SI) engine, accurate measurements of the local instantaneous heat flux are wanted. An improved understanding will lead to better heat transfer modelling, which will improve the accuracy of current simulation software. In this research, prototype thin film gauge (TFG) heat flux sensors are used to capture the transient in-cylinder heat flux within a Cooperative Fuel Research (CFR) engine. A two-zone temperature model is linked with the heat flux data. This allows the distinction between the convection coefficient in the unburned and burned zone.

Homogeneous Charge Compression Ignition (HCCI) engines can achieve both a high thermal efficiency and near-zero emissions of NOx and soot. However, their maximum attainable load is limited by the occurrence of a ringing combustion. At high loads, the fast combustion rate gives rise to pressure oscillations in the combustion chamber accompanied by a ringing or knocking sound. In this work, it is investigated how these pressure oscillations affect the in-cylinder heat transfer and what the best approach is to model the heat transfer during ringing combustion. The heat transfer is measured with a thermopile heat flux sensor inside a CFR engine converted to HCCI operation. A variation of the mass fuel rate at different compression ratios is performed to measure the heat transfer during three different operating conditions: no, light and severe ringing. The occurrence of ringing increases both the peak heat flux and the total heat loss.

To optimize internal combustion engines (ICEs), a good understanding of engine operation is essential. The heat transfer from the working gases to the combustion chamber walls plays an important role, not only for the performance, but also for the emissions of the engine. Besides, thermal management of ICEs is becoming more and more important as an additional tool for optimizing efficiency and emission aftertreatment. In contrast little is known about the convective heat transfer inside the combustion chamber due to the complexity of the working processes. Heat transfer measurements inside the combustion chamber pose a challenge in instrumentation due to the harsh environment. Additionally, the heat loss in a spark ignition (SI) engine shows a high temporal and spatial variation. This poses certain requirements on the heat flux sensor. In this paper we examine the heat transfer in a production SI ICE through the use of Thin Film Gauge (TFG) heat flux sensors.

In the development of internal combustion engines, measurements of the heat transfer to the cylinder walls play an important role. These measurements are necessary to provide data for building a model of the heat transfer, which can be used to further develop simulation tools for engine optimization. This research will focus on the Thin Film Gauge (TFG) heat flux sensor. This sensor consists of a platinum RTD (Resistance Temperature Detector) on an insulating Macor® (ceramic) substrate. The sensor has a high frequency response (up to 100 kHz) and is small and robust. These properties make the TFG sensor adequate for measurements in the combustion chamber of an internal combustion engine. To use this sensor, its thermal properties - namely the temperature sensitivity coefficient and the thermal product - must be correctly calibrated. First, different calibration setups with a different temperature range are used to calibrate the temperature sensitivity coefficient of the TFG sensor.

Homogeneous charge compression ignition (HCCI) engines are a promising alternative to traditional spark- and compression-ignition engines, due to their high thermal efficiency and near-zero emissions of NOx and soot. Simulation software is an essential tool in the development and optimization of these engines. The heat transfer submodel used in simulation software has a large influence on the accuracy of the simulation results, due to its significant effect on the combustion. In this work several empirical heat transfer models are assessed on their ability to accurately predict the heat flux in a CFR engine during HCCI operation. Models are investigated that are developed for traditional spark- and compression-ignition engines such as those from Annand [1], Woschni [2] and Hohenberg [3] and also models developed for HCCI engines such as those from Chang et al. [4] and Hensel et al. [5].

The need for simulation tools for the internal combustion engine is becoming more and more important due to the complex engine design and increasingly strict emission regulation. One needs accurate and fast models, but fuels consist of a complex mixture of different molecules which cannot realistically be handled in computations. Simplifications are required and are realized using fuel surrogates. The main goal of this work is to show that the choice of the surrogates is of importance if simplified models are used and that the performance strongly depends upon the sensitivity of the fuel properties that refer to the main model hypotheses. This paper starts with an overview of surrogates for diesel and bio-diesel as well as the motivation for choosing them. Next, a phenomenological model for vaporizing fuel-sprays is implemented to assess how well-known surrogates for diesel and bio-diesel affect the obtained results.

In this work a new design of a liquid fuelled combustion engine is proposed for small and light weight unmanned air vehicles (<10kg and 15-200N thrust). Ethanol and gasoline were selected as the potential fuels while pressurized air and hydrogen peroxide were used as the oxidizer. The engine combines features of both a common rocket and turbojet engine. The main features of the engine are the restart ability during flight, low cost, easy manufacturability, light weight, long operation time and high durability. The main difficulties that come along with this engine are the need for proper engine cooling (long term operation) and start-up ability at atmospheric conditions. The low temperatures and injection pressures are not favorable for the fuel atomization and ignition. The paper focuses on the design on low pressure injectors and a start-up mechanism for micro UAV's without the use of a large amount of additional fueling circuits or components.

Diesel spray experimentation at controlled high-temperature and high-pressure conditions is intended to provide a more fundamental understanding of diesel combustion than can be achieved in engine experiments. This level of understanding is needed to develop the high-fidelity multi-scale CFD models that will be used to optimize future engine designs. Several spray chamber facilities capable of high-temperature, high-pressure conditions typical of engine combustion have been developed, but because of the uniqueness of each facility, there are uncertainties about their operation. The Engine Combustion Network (ECN) is a worldwide group of institutions using combustion vessels, whose aim is to advance the state of spray and combustion knowledge at engine-relevant conditions. A key activity is the use of spray chamber facilities operated at specific target conditions in order to leverage research capabilities and advanced diagnostics of all ECN participants.

Fuel atomization and combustion at engine-like conditions are complicated and sensitive processes which make it hard to perform quantitative experiments with high precision and reproducibility. A better understanding of the processes can be obtained by controlling the boundary conditions. Variable parameters with an important influence on the sprays include fuel temperature, chamber temperature, injection pressure, gas velocity. Controlling all these parameters in an experimental setup is not evident since a lot of them fluctuate with time or interact with each other. Constant volume combustion chambers, using the pre-combustion method, have already shown to be a useful experimental tool for this kind of research purposes. The obtained quantitative results can in a next step be used to evaluate either multi-dimensional or simplified lower dimensional models.