Energy distribution strategy of power split marine hybrid energy storage propulsion system

The marine industry faces significant challenges, including the energy crisis and environmental pollution. In response, marine hybrid technology is regarded as an effective solution to address these issues. However, the overall performance of such systems is primarily governed by the energy management strategy. Therefore, this research proposes a marine hybrid energy management strategy (EMS) based on an adaptive migration butterfly optimization algorithm (AMBOA). Firstly, the performance index function is extended by adding a weighting term that suppresses the rate of change of the output power of the natural gas engine based on the Equivalent Consumption Minimization Strategy (ECMS), as well as maintaining the SOC penalty function to operate the powertrain in a quasi-static mode. Afterwards, Particle swarm algorithm is introduced to solve the problem that the butterfly optimisation algorithm is prone to fall into local optimum, and then the adaptive migration butterfly optimisation algorithm is formulated. Finally, the effectiveness of the proposed strategy is verified by the simulation platform and test bench. The results revealed that AMBOA-EMS effectively suppressed the frequent fluctuations of natural gas engine power compared to ECMS-EMS on the test stand, while saving 5.59 % of fuel while ensuring the power.

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Publication Details

Journal
Alexandria Engineering Journal
Published
2025-04-04
DOI
https://doi.org/10.1016/j.aej.2025.03.108
Citations
2
Primary Topic
Maritime Transport Emissions and Efficiency
Type
article
Field-Weighted Citation Impact
1.60
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article

Energy distribution strategy of power split marine hybrid energy storage propulsion system

Xiaojun Sun, Gang Li, Fengmei Xin
2 citations
Alexandria Engineering Journal
Maritime Transport Emissions and Efficiency
1.60
article

Energy distribution strategy of power split marine hybrid energy storage propulsion system

Xiaojun Sun, Gang Li, Fengmei Xin
article en
2 citations

Abstract

The marine industry faces significant challenges, including the energy crisis and environmental pollution. In response, marine hybrid technology is regarded as an effective solution to address these issues. However, the overall performance of such systems is primarily governed by the energy management strategy. Therefore, this research proposes a marine hybrid energy management strategy (EMS) based on an adaptive migration butterfly optimization algorithm (AMBOA). Firstly, the performance index function is extended by adding a weighting term that suppresses the rate of change of the output power of the natural gas engine based on the Equivalent Consumption Minimization Strategy (ECMS), as well as maintaining the SOC penalty function to operate the powertrain in a quasi-static mode. Afterwards, Particle swarm algorithm is introduced to solve the problem that the butterfly optimisation algorithm is prone to fall into local optimum, and then the adaptive migration butterfly optimisation algorithm is formulated. Finally, the effectiveness of the proposed strategy is verified by the simulation platform and test bench. The results revealed that AMBOA-EMS effectively suppressed the frequent fluctuations of natural gas engine power compared to ECMS-EMS on the test stand, while saving 5.59 % of fuel while ensuring the power.

Alexandria Engineering JournalVol. 124
Liaoning University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 19%
Maritime Transport Emissions and Efficiency
1.60
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Energy distribution strategy of power split marine hybrid energy storage propulsion system — Xiaojun Sun, Gang Li, et al. · Alexandria Engineering Journal (2025) | TGRS Research Map | TGRS