There is increasing pressure to reduce well-to-wheel CO2 emissions in the internal combustion engine (ICE). This will require improvements in engine technology. An important aspect will include identification of the right fuel to match the new ICE’s requirements. It will likely require fuel production to move away from current production types. This is an additional optimisation that refineries will have to consider along with the other factors they balance to remain profitable.
The use of additives is a key enabler to ensure that the fuels produced are fit-for-purpose whilst increasing refinery flexibility and hence profitability. However, for fuels, such as diesel, it has proved difficult to understand the variability of additive response with changes in fuel composition. This is particularly true for the cold flow response where subtle differences in fuels can impact additive appetite.
This paper describes how we have employed novel systematic ways of characterising and analysing diesel to identify the key parameters that impact fuel additive response. How, with the use of modern formulation methodology, we have built an understanding of additive response, constructing models for additive performance. This in turn will enable the development of models to allow refineries to predict the impact of changes made in their fuel production.
These tools will allow refineries to conduct scenario planning, to identify what the impact of variations in their production will have on their economics. Selection of the right blend of additive technology, refinery processes, and crude sources, will aid refineries to profitably produce the types of fuel required, for the new ICE technology to reduce vehicle well-to-wheel CO2 emissions.