复合绿色能源无人艇初步总体优化设计
毕业论文关键词：W型槽道无人艇；绿色能源；模型制作；综合优化；遗传算法
Abstract As a new concept, USV can be widely used in patrolling, reconnaissance, surveillance, counter-terrorism attack and other dangerous tasks. Countries around the world are designing and developing different kinds of USV actively. The main object of this study is based on a W-type channel USV. When channel hydroplane run at high speed, the air enter in punching action from the bow portion of the groove, and mix with the inner channel water as a gas-water mixture. With the speed getting higher, the amount of intake air get more, the formation of an air layer get easier. For the density of air or air-water mixture is much smaller than the water, the air layer can lubricate the channel which effect on the sliding surface top, reducing resistance of the hull greatly. At the same time , the shape of the hull which lifting the hull out of the water can provide Lift force, improving efficiency. Therefore, we use W-type channel USV as experimental ship. Firstly， we establish a mathematical model of the ship. AS Ship design is a multi-variable, multi-target, multi-complex process constraints, we should study speed, maneuverability, sea-keeping performance , solar energy output to objective function, constraints to determine the conditions and select the design variables. GA algorithm has also been used to establish mathematical models to optimize the calculation and analysis. Secondly, we do arrangement demonstration and detailed design of clean energy systems of W-type channel USV including a kind of solar system, hydrofoils-pillars control system ，selecting and demonstrating superstructure of ship where solar panels arranged. After that, based on the optimized data obtained, we do detailed design and calculations of the W-type channel USV, and produce a model of it which with composite clean energy system . Finally, we do some basic experiments and analyze the result of it, and conducte a system identification of rolling test.
Keywords: W-type channel USV; Clean Energy; Model Production; Integrated Optimization; Genetic Algorithm;