optimization of marine main engine based on comprehensive objective of speed and real-time energy efficiency

doi:10.16411/j.cnki.issn1006-7736.2020.03.007

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Journal of Dalian Maritime University ›› 2020, Vol. 46 ›› Issue (3) : 60-67. DOI: 10.16411/j.cnki.issn1006-7736.2020.03.007

SUN Chao^{*1, 2}, ZHANG Jun-dong¹, LIU Chao²

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Abstract

In the actual navigation environment, through the real-time optimization of the ship’s main engine speed, the ship’s energy-saving and carbon emission reduction effect can be improved. Therefore, the real-time energy efficiency operation index was derived as the monitoring index, and the comprehensive objective function of comprehensive speed deviation and realtime energy efficiency operation index(EEOI) deviation was proposed. Taking “Yuming” as an example, BP neural network was used to predict the main engine fuel consumption rate and ship speed, and genetic algorithm was used to optimize the main engine speed. Simulation results show that the real-time EEOI is more sensitive to the variation of navigation environment and suitable for real-time energy efficiency monitoring; the error of prediction model of ship speed and main engine fuel consumption rate base on BPNN is less than 2%; it’s more convenient to achieve the objective of fuel saving and carbon emission reduction by adopting the comprehensive objective function; the smaller the weight of ship speed is, the more obvious the reduction of EEOI is; the optimized revolution can be obtained in around 10 epochs by genetic algorithm. The proposed method can improve the energy saving and emission reduction effect of the main engine under the given speed limit requirements and navigation environmental conditions.

Key words

marine main engine / ship speed optimization / energy efficiency operation index (EEOI) / neural network / genetic algorithm

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SUN Chao, ZHANG Jun-dong, LIU Chao. optimization of marine main engine based on comprehensive objective of speed and real-time energy efficiency[J]. Journal of Dalian Maritime University. 2020, 46(3): 60-67 https://doi.org/10.16411/j.cnki.issn1006-7736.2020.03.007

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