Fuel identification: Verifierad bränsleanvändning inom tunga vägtransporter
Rapport, 2025
The project "Fuel identification - Verified fuel use in heavy road transport" investigated which technologies can be viable to identify the fuel in heavy trucks’ tanks. It is likely that a large number of trucks that can run on fossil fuels will be in operation long after 2030. In order to be able to detect that trucks, which are mandated to be solely powered by renewable fuels, are actually using these, technical solutions must be developed that can perform such detection safely, cost-effectively and on a vehicle level. The project shows that viable and available technologies can be divided into 3 main categories: - Physical sensors, which directly measure the properties of the fuel and thus can detect differences between different fuels. - Smart detectors, in which sensors already in the vehicle are used to measure the properties of different fuels after an initial mapping. - Digital twins, where the entire refueling ecosystem, including petrol stations, vehicles, payment systems and supply chains, can be replicated. Fuel labelling was also explored but rejected as an option for this purpose. During the project, a literature study and two open workshops were conducted. The analysis of the different technologies shows that solutions already exist in practice. However, there are also challenges, such as the cost and complexity of retrofitting physical sensors into the existing fleet, as well as complicated modeling and access to large amounts of training data for smart detectors and digital twins. The project was financed through Trafikverket within the framework of Triple F and in-kind from the expert group. The project group consisted of Matthias Schmitz, Fredrik Hildor and Pontus Bokinge (CIT Renergy), Jonathan Converse (Chalmers Industriteknik), Beatriz Cabrero-Daniel and Christian Berger (University of Gothenburg) and Jonas Sjöblom (Chalmers University of Technology) and received support from the expert group consisting of Mats Hultman (Neste), Monica Johansson and Anna Lutz (Volvo Trucks Technology), Jonas Strömberg (Scania), Liene Norberg (Biofuel Express), Magnus Nyfjäll (Colabit) and Pär Forsberg (Consat).
digital twins
neural networks
CO2 emissions allocation
e-fuels
fuel sensors
biofuels
Fuel identification