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.


Wengang Mao (kontakt)

Biträdande professor vid Chalmers, Mekanik och maritima vetenskaper, Marin teknik

Leif Eriksson

Docent vid Chalmers, Rymd-, geo- och miljövetenskap, Mikrovågs- och optisk fjärranalys



Finansierar Chalmers deltagande under 2016–2017

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