Marine transportation sector is highly dependent on fossil-based energy carriers.
Decarbonization of shipping can be accomplished by implementing biobunkers into
an existing maritime fuel supply chain. However, there are many compatibility
issues when blending new biocomponents with their fossil-based counterparts.
Thus, it is of high importance to predict the effect of fuel properties on
marine engine performance, especially for new fuel blends. In the given work,
possible future solutions concentrated on liquid fuels are taken into account.
Under consideration are such fuels as biodiesel (FAME), hydrotreated vegetable
oil (HVO), straight vegetable oil (SVO), pyrolysis oil, biocrude, and methanol.
Knowledge about the behavior of new fuel in an existing engine is notably
important for decision makers and fuel producers. Hence, the main goal of the
present work is to create a model, which can predict the engine performance from
the end-user perspective. For the purpose of modeling, only the latest research
on marine fuels is taken into account. In the current approach, results from a
representative measurement set-up are compared in order to create a uniform
model. As a result, all the provided data are expressed in relative changes in
reference to standard marine fuel – heavy fuel oil (HFO). The modeling Is
performed by means of multilinear regression and accuracy of the model is
relatively high, with a coefficient of determination over 0.9. The outcomes
provide a prediction of final engine performance for the specified fuel blend.
Knowing the final properties of fuel (such as calorific value, density,
viscosity), it is attainable to estimate fuel consumption, carbon dioxide
emissions and determine possible fuel compatibility issues. Moreover, the model
enables estimation of carbon dioxide (CO2) tailpipe
emissions, which should be included in the whole Life Cycle Analysis (LCA) while
assessing the renewability index of the fuel.