부산대학교 도서관

In the maritime and shipping industries, there is a growing demand for environmentally friendly ships due to increasingly stringent environmental regulations. Hybrid ships, which alter propulsion methods to achieve eco-friendliness, are one such solution. These ships integrate auxiliary power sources with conventional mechanical propulsion systems to optimize engine operating points and enhance propulsion performance. However, hybrid electric propulsion systems are mechanisms that maximize performance by assisting in the efficiency of the main power source through an auxiliary power source, and the efficiency can vary greatly depending on the operation of each power source. Therefore, an optimal power control strategy is needed to maximize efficiency. Heuristic-based control strategies are widely used in hybrid electric vehicles and various industries due to their simplicity and computational efficiency. However, they rely on experiential rule-based definitions, which can lead to suboptimal performance. In this study, to overcome these limitations and increase the energy efficiency of hybrid electric propulsion ships through the exploration of improved control strategies, a global optimization algorithm called Dynamic Programming (DP) is applied to the power control problem to derive a global optimal solution, and an improved heuristic control strategy is established through regression using sigmoid and polynomial functions. The improved control strategy ensures that hybrid power distribution comes closer to global optimality under various SOC conditions, thereby enhancing overall energy efficiency. To evaluate the proposed strategy, a simulator developed for performance assessment of hybrid electric propulsion ships was used. A comparison with the results of the existing heuristic-based strategy confirmed a possibility of improvement of about 9% in fuel efficiency. The results of this study will contribute as basic data for improving fuel efficiency of hybrid electric propulsion ships in the design stage.