Optimizing energy management strategies in marine hybrid propulsion systems using an upgraded particle swarm optimization-based approach

In light of the formidable energy crisis and environmental pollution challenges facing the maritime industry, the adoption of hybrid propulsion technology emerges as a promising mitigation strategy. However, the overall effectiveness of this approach hinges upon the meticulous design of energy management strategies. Therefore, this study introduces an enhanced iteration of the Particle Swarm Optimization (PSO) algorithm tailored for optimizing energy management strategies in marine hybrid propulsion systems. Initially, taking inspiration from the Equivalent Consumption Minimization Strategy (ECMS) employed in hybrid vehicles, we introduce a multi-objective performance metric with the objective of optimizing economic and dynamic facets. These objectives are centered on reducing fuel consumption and minimizing the frequency of engine operations. Subsequently, to mitigate the tendency of PSO to converge to local optima, we integrate the Gray Wolf Optimization (GWO) algorithm, leading to the refinement of the PSO algorithm. Finally, we conduct a comprehensive evaluation of the proposed Upgraded Particle Swarm Optimization-based Energy Management Strategy (UPSO-EMS) under diverse operating conditions to assess its performance. The findings substantiate that UPSO-EMS can deliver an additional fuel savings rate ranging between 2.84% and 7.60%.