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

Authors: Yingbin Chen; Sheng Ji; Guoxiang Dong; Yiyan Wen; Jipan Qiao

Addresses: State Key Laboratory of Maritime Technology and Safety, Shanghai Ship and Shipping Research Institute Co., Ltd., Minsheng Road, Pudong, Shanghai, China ' State Key Laboratory of Maritime Technology and Safety, Shanghai Ship and Shipping Research Institute Co., Ltd., Minsheng Road, Pudong, Shanghai, China ' State Key Laboratory of Maritime Technology and Safety, Shanghai Ship and Shipping Research Institute Co., Ltd., Minsheng Road, Pudong, Shanghai, China ' State Key Laboratory of Maritime Technology and Safety, Shanghai Ship and Shipping Research Institute Co., Ltd., Minsheng Road, Pudong, Shanghai, China ' State Key Laboratory of Maritime Technology and Safety, Shanghai Ship and Shipping Research Institute Co., Ltd., Minsheng Road, Pudong, Shanghai, China

Abstract: 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.

Keywords: fuel consumption model; speed optimisation; carbon intensity indicator; CII; grey box model; GBM; white box model; WBM; black box model; BBM.

DOI: 10.1504/IJSTL.2025.147551

International Journal of Shipping and Transport Logistics, 2025 Vol.20 No.4, pp.496 - 527

Received: 07 Oct 2023
Accepted: 30 Apr 2024
Published online: 21 Jul 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article