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All Journal International Journal of Marine Engineering Innovation and Research
Rachmat Subagyo
Departement of Mechanical Engineering, Universitas Lambung Mangkurat, Banjarmasin, 70123, Indonesia.
Automotive Engineering Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Transportation

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A Machine Learning-Based Approach for Designing SEEMP on Ships: Case Study of CO₂ Emissions at a Container Port Elwas Cahya Wahyu Pribadi; Abdul Ghofur; Rachmat Subagyo; Ma’ruf; Akhmad Syarief; Aldinor Setiawan
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 4 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i4

Abstract

The management of ship energy significantly affects both cost efficiency such as earnings before interest and environmental sustainability, particularly in reducing CO₂ emissions produced by ship operations. Despite the importance of this issue, research on ship energy consumption within container terminals remains limited. This study aims to estimate CO₂ emissions generated by ship activities in container ports, focusing on emission variables related to the Ship Energy Efficiency Management Plan (SEEMP). The calculation considers active ship movements in the port, including approach, maneuvering, and berthing processes. Energy consumption and CO₂ emissions were analyzed using random forest regression (RF) with default settings, and the model’s accuracy was validated through k-fold cross-validation. The results identified five major factors influencing CO₂ emissions: (1) main engine power, (2) auxiliary engine power, (3) waiting time in the port, (4) maneuvering time, and (5) berthing time. Among these, maneuvering, waiting, and berthing showed the highest significance, confirmed by attribute selection and validation results. The random forest model demonstrated a prediction accuracy of 98.89%, confirming its reliability. Moreover, operational fuel efficiency analysis indicated that combining voyage optimization, skilled operators, and cold ironing facilities could reduce CO₂ emissions by up to 20%. These findings provide valuable insights and serve as a foundation for developing a more effective Ship Energy Efficiency Management Plan to enhance environmental performance in maritime operations.
Energy Management Strategies for Hybrid Ship Propulsion: A Systematic Review of MPC, ECMS, and Predictive Control Abdul Ghofur; Elwas Cahya Wahyu Pribadi; Rachmat Subagyo; Mastiadi Tamjidillah; Ma’ruf
International Journal of Marine Engineering Innovation and Research Vol. 11 No. 2 (2026)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v11i2

Abstract

Effective energy management is critical for maximizing the efficiency and environmental benefits of hybrid propulsion systems (HPS) in ships. This systematic review evaluates various advanced energy management strategies (EMS) applied to marine HPS, focusing on model predictive control (MPC), equivalent consumption minimization strategy (ECMS), sequential quadratic programming (SQP), predictive power-split, and rule-based approaches. Based on an analysis of recent international literature, findings indicate that MPC-based EMS improves fuel efficiency by 10-20% and extends battery life through optimal power distribution under dynamic load conditions. Meanwhile, ECMS reduces equivalent fuel consumption by up to 25% under varying operational cycles. Predictive power-split algorithms achieve 15-20% energy savings by anticipating propulsion load changes up to 30 minutes in advance. Compared to conventional rule-based systems, advanced EMS reduces CO₂ emissions by 20-45% and NOx emissions by 20-60%, especially during harbor maneuvering and low-speed cruising. However, challenges remain, including high computational demands for real-time MPC, dependence on accurate load prediction models, and the lack of standardized interoperability protocols. This review concludes that integrating artificial intelligence and digital twins into EMS represents the most promising research direction. For ferries, patrol boats, and research vessels, implementing MPC or ECMS with adaptive tuning can significantly enhance operational performance while complying with IMO EEDI and CII regulations.
Evolution and Innovation of Ship Propulsion Technology: From Paddle Power to Electric and Wind-Assisted Hybrid Systems for a Sustainable Maritime Future Mastiadi Tamjidillah; Elwas Cahya Wahyu Pribadi; Abdul Ghofur; Rachmat Subagyo; Ma’ruf
International Journal of Marine Engineering Innovation and Research Vol. 11 No. 2 (2026)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v11i2

Abstract

Ship propulsion has evolved significantly over thousands of years, from the use of simple paddles around 40,000 BCE to modern advanced systems driven by diesel engines, steam turbines, nuclear reactors, electric motors, and wind power. This systematic literature review aims to synthesize current knowledge on ship propulsion systems, highlighting technological advancements, energy efficiency, and environmental impacts. By analyzing various studies through a qualitative approach and the PRISMA framework, this research identifies three main themes: advanced propulsion systems, propulsion optimization, and hybrid technology integration. The results show that while diesel engines remain dominant, Integrated Full Electric Propulsion (IFEP) systems coupled with induction motors and Permanent Magnet Synchronous Motors (PMSMs) offer higher efficiency and lower emissions. Furthermore, wind-assisted technologies, such as Dynarigs, Flettner rotors, and towing kites, demonstrate great potential to reduce fuel consumption by up to 50% compared to conventional systems, while nuclear propulsion enables higher operational speeds with minimal fuel replenishment. However, key challenges remain, including high initial investment costs, control system complexity, and regulatory acceptance. In conclusion, the future of ship propulsion lies in hybrid configurations that optimize the combination of electric and wind power, supported by predictive computational models and fault-tolerant control to achieve cleaner, safer, and more sustainable maritime operations. Interdisciplinary collaboration is essential to accelerate this transition.
Co-Authors Abdul Ghofur Abdul Ghofur Akhmad Syarief Aldinor Setiawan Elwas Cahya Wahyu Pribadi Mastiadi Tamjidillah Ma’ruf