Fuel consumption model of marine main engine and speed optimisation based on carbon intensity indicator

With the introduction of the carbon intensity indicator (CII) for international shipping and its official implementation on January 1, 2023, energy conservation, emission reduction and green development of the shipping industry have once again attracted much attention. In order to further improve the efficiency of ship energy consumption, the grey box model (GBM) coupled with ship physical characteristics and machine learning algorithm is proposed and compared with the white box model (WBM) and the black box model (BBM). Based on the grey box model of random forest (GBM RF), a new strategy for ship speed optimisation is proposed. The experimental results show that the performance of WBM is poor, and BBM has the highest prediction accuracy when the number of sample data is large. GBM can encapsulate the mechanical method of WBM into BBM, so as to achieve the same performance of BBM. Especially when the number of samples is small, GBM performs satisfactorily. In addition, the results show that GBM can be used as an effective tool for ship speed optimisation.