Ship performance modelling through big data techniques (SPLINE)
Forskningsprojekt, 2016
– 2017
Due to the increased awareness of air emissions and economic impact from energy consumption in shipping, as well as stricter environmental regulations, the maritime community is seeking for solutions to increase energy efficiency burning less fuel. According to a comprehensive survey of the entire shipping market by DNVGL1, the most promising measures aiming at reducing fuel consumption are the voyage optimisation for a ship’s sail planning and ship performance monitoring during sailing in seaways. One of the key components of the two measures is the so-called fuel consumption model, which should describe accurately a ship’s fuel consumption rate in terms of different weather and operation conditions. The fuel consumption model could be implemented in a sail plan system to predict fuel cost along different potential routes, and help to determine the optimised route with lowest fuel cost. The predicted fuel cost for certain operation conditions could also be compared with the actual cost to monitor a ship’s energy performance and guide a ship’s navigation.
Deltagare
Wengang Mao (kontakt)
Chalmers, Mekanik och maritima vetenskaper, Marin teknik
Leif Eriksson
Mikrovågs- och optisk fjärranalys
Finansiering
Chalmers
Finansierar Chalmers deltagande under 2016–2017
Relaterade styrkeområden och infrastruktur
Informations- och kommunikationsteknik
Styrkeområden
Hållbar utveckling
Drivkrafter
Transport
Styrkeområden
Energi
Styrkeområden
Innovation och entreprenörskap
Drivkrafter