Development of a fuzzy control system for optimizing fuel consumption on ship main propulsion engines

The maritime industry faces increasing pressure to enhance fuel efficiency and reduce greenhouse gas emissions. Traditional control methods often fail to adapt dynamically to varying sea conditions, leading to suboptimal fuel consumption. This study proposes a fuzzy logic control (FLC) system to optimize fuel consumption in ship main propulsion engines by dynamically adjusting engine parameters based on real-time operational data. The developed FLC model considers key input variables such as engine load, ship speed, and fuel injection timing. The fuzzy inference system comprises fuzzification, rule base, and defuzzification stages. A simulation was conducted in MATLAB/Simulink to evaluate the effectiveness of the FLC compared to conventional control strategies. Simulation results demonstrate that the proposed system significantly improves fuel efficiency. Compared to traditional PID controllers, the FLC system achieves a 5-10% improvement in fuel consumption under various operating conditions. The adaptability of the FLC allows for better fuel optimization and reduction in CO2 emissions. The proposed FLC system effectively enhances fuel efficiency and can be implemented in marine propulsion systems to support sustainable shipping operations. Future research will focus on integrating machine learning techniques to further refine control precision.