Optimal Design of Propulsion System Configuration for Electrically Propelled Unmanned Surface Vehicle

Abstract

Unmanned surface vehicles (USVs) are vessels that operate without any crew onboard. There is an increased demand for USVs in recent years, particularly for the use of water quality monitoring and ocean data mapping. In China, USVs are widely used as a luring fish boat which acts as the assisting boat of light luring seine vessel. One of the main problems of such boat is that the traditional propulsion system is poorly matched with the high energy consumption that is required during certain specific operation, which results in poor vessel performance. A hybrid electric propulsion system configuration solution is proposed to increase the overall propulsion efficiency of such USVs. The typical operating profile was identified and a comprehensive simulation was conducted to demonstrate the compatibility during vessel operations. An intelligent equipment selection analysis was also carried out to recommend the optimal equipment selection by considering a multiobjective problem. The result shows that the configuration solution proposed can reduce fuel consumption and the optimal intelligent selection method can provide a suitable selection solution for decision makers. This article highlights an energy management strategy focusing on the threshold method based on support vector machine pattern recognition. A multiobjective particle swarm optimization algorithm based on the dynamic inertia weight and chaotic motion was used to optimize the equipment selection by considering fuel consumption and emissions. The proposed propulsion system configuration and equipment selection solution can be implemented for the design of USVs, which has a routine fixed operating pattern.