Search Results

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.

Knock is one of the main factors limiting the efficiency of spark-ignition engines. The introduction of alternative fuels with elevated knock resistance could help to mitigate knock concerns. Alcohols are prime candidate fuels and a model that can accurately predict their autoignition behavior under varying engine operating conditions would be of great value to engine designers. The current work aims to develop such a model for neat methanol. First, an autoignition delay time correlation is developed based on chemical kinetics calculations. Subsequently, this correlation is used in a knock integral model that is implemented in a two-zone engine code. The predictive performance of the resulting model is validated through comparison against experimental measurements on a CFR engine for a range of compression ratios, loads, ignition timings and equivalence ratios.

Using liquid alcohols, such as methanol and ethanol, in spark-ignition engines is a promising approach to decarbonize transport and secure domestic energy supply. Methanol and ethanol are compatible with the existing fuelling and distribution infrastructure and are easily stored in a vehicle. They can be used in internal combustion engines with only minor adjustments and have the potential to increase the efficiency and decrease noxious emissions compared to gasoline engines. In addition, methanol can be synthesized from a wide variety of sources, including renewably produced hydrogen in combination with atmospheric CO₂. Presently, during the production of ethanol or methanol a dehydration step is always applied. This step accounts for a significant part of the entire production process' energy consumption and thus, from an economical point of view, methanol and ethanol could become more interesting alternative fuels if the costs related with dehydration could be reduced.

Hydrogen-fuelled internal combustion engines are an attractive alternative to current drive trains, because a high efficiency is possible throughout the load range and only emissions of oxides of nitrogen (NOx) can be emitted. The latter is an important constraint for power and efficiency optimization. Optimizing the engine with experiments is time consuming, so thermodynamic models of the engine cycle are being developed to speed up this process. Such a model has to accurately predict the heat transfer in the engine, because it affects all optimization targets. The standard heat transfer models (Annand and Woschni) have already been cited to be inaccurate for hydrogen engines. However, little work has been devoted to the evaluation of the flow-field based heat transfer model, which is the topic of this paper. The model is evaluated with measurements that focus on the effect of the fuel, under motored and fired operation.