Due to tightening regulations on exhaust emissions from ships, there is a growing need to develop electric or hybrid electric propulsion systems to replace conventional diesel-based ship power systems. The hybrid electric propulsion system is suitable for small and medium-sized vessels and its energy efficiency significantly depends on the arrangement of different power sources, power control strategies for energy sources, and energy storage system (ESS). Therefore, an analytical simulation to evaluate the energy efficiency of ships with their structure and control strategies is needed. In this study, a back–forward approach-based efficiency performance analysis model was developed using the Holtrop–Mennen resistance model to calculate ship resistance and power demand based on a given ship’s speed profiles. This model has the advantages of using easily obtainable ship speed profiles as the input and can be modularized for each power source and ESS, incorporating mechanical performance limitations, and allows for rapid analysis. The developed analytical model was applied to a hybrid electric propulsion system in a marine support vessel and its energy efficiency was evaluated by establishing rule-based power control strategies. As a result, the engine efficiency of the hybrid electric propulsion system increased from about 27% to 30% compared to the existing system, and the final effect of reducing fuel consumption by about 10% compared to the existing system was confirmed through the developed simulator. In the future, this analytical model could be utilized to derive the optimal layout of hybrid electric propulsion systems, and to formulate power control strategies.

The interest in wind-assisted ship propulsions (WASPs) is increasing to improve fuel efficiency and to reduce greenhouse gas emissions in ships. A rotor sail, one of the typical WASPs, can provide auxiliary propulsive force by rotating a cylinder-shaped structure based on the Magnus effect. However, due to its huge rotating structure, a meticulous evaluation of the influence on the ship structure and dynamical stability of the rotating structure should be conducted in the design stage. In this respect, an analysis of the rotating structure for a 30 m height and 3 m diameter rotor sail was conducted in this study. First, a 4DOF (four-degree-of-freedom) model was derived to simplify the dynamics of the rotor sail. Using the 4DOF model, natural frequencies for four low-order modes of the rotor sail were calculated, and frequency responses at support points were predicted. Next, a comparison and validation with the finite element model of the rotor sail were carried out. For the 1st and 2nd natural frequencies, a difference of approximately 0.3 Hz was observed between the 4DOF model and the finite element model, confirming the effectiveness of the 4DOF model for low-order modes. In analysis with changes in the bearing supporting stiffnesses, it was verified that lower support bearings have a significant impact on rotor dynamics compared to upper support bearings. Vibration response at the upper support was also confirmed through frequency response analysis caused by imbalance at Thom disk and mid-plate. Additionally, when estimating the eccentricity of the Thom disk as imbalance, a limit of eccentricity error could be set as 24 mm. The presented modeling procedures and analysis results can be references during early design stage of a novel rotor sail structure.

Since power demand varies due to uncertain environmental conditions, a deterministic power control strategy for hybrid electric propulsion ships contains a limitation in securing robust performance. To overcome this limitation, this study applies a stochastic power control strategy based on the augmented operational dataset. This study generated 150 datasets and derived the optimal control strategy set using a dynamic programming algorithm. By synthesizing a set of optimal control strategies, we divided them into a total of 10 bins according to the battery state of charge (SOC) and implemented a probabilistic map for the power distribution ratio according to the demanded power in each bin. Additionally, the memory and SOC correction factor were utilized to prevent frequent changes in power control and ensure that the SOC remains stable. This strategy resulted in a 3% improvement in efficiency compared to the deterministic method. In addition, it can be implemented in a real-time strategy utilizing stochastic maps.