Singapore Institute of Technology
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Rule-Based Control Studies of LNG–Battery Hybrid Tugboat

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journal contribution
posted on 2023-12-01, 03:37 authored by Sharul Baggio Mohamed RoslanSharul Baggio Mohamed Roslan, Zhi Yung TayZhi Yung Tay, Dimitrios Konovessis, Joo Hock Ang, Nirmal Vineeth Menon

The use of hybrid energy systems in ships has increased in recent years due to environmental concerns and rising fuel prices. This paper focuses on the development and study of a hybrid energy system using liquefied natural gas (LNG) and batteries for a tugboat. The hybrid system model is created in MATLAB/Simulink® and uses fuel data obtained from an operational diesel-powered tugboat. The LNG–hybrid system is then subjected to testing in four distinct configurations: fixed speed, variable speed, and with and without a battery. The different configurations are compared by computing the daily fuel cost, CO2 emissions, energy efficiency operation indicator (𝐸𝐸𝑂𝐼) and carbon intensity indicator (𝐶𝐼𝐼) ratings in three distinct operation cases. The analysis reveals that the use of an LNG–battery hybrid tugboat results in an average reduction of 67.2% in CO2 emissions and an average decrease of 64.0% in daily fuel cost compared to a diesel system. An energy management system using rule-based (RB) control is incorporated to compare the daily cost and CO2 emissions for one of the case studies. The rule-based control that requires the battery to be used and the LNG engine to be switched off at the lowest allowable minimum power based on the specific gas consumption produces the most cost-effective control strategy out of all the different control strategies tested. The result demonstrates that an additional reduction of CO2 and daily fuel cost for LNG–battery hybrid tugboats by 23.8% and 22.3%, respectively, could be achieved with the implementation of the cost-effective strategy as compared to not having a control strategy.


MOE, Grant Number R-MOE-A403-E002

MOE, Grant Number R-MOE-E103-F010


Journal/Conference/Book title

Journal of Marine Science and Engineering

Publication date



  • Post-print

Project ID

  • 7859 (R-MOE-A403-E002) Remote Monitoring of Hybrid Power and Propulsion Systems for Smart Ships
  • 22 (R-MOE-E103-F010) Sustainable Marine Transport: Ship Energy Systems & Environmental Technologies

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