摘要
风帆攻角决策是风帆助航船充分利用风能的关键。在船舶航行过程中,风帆产生助推力的同时也产生侧推力,引起船舶偏航和能效降低。针对该问题,本文引入侧推权重因子,建立由助推力系数与侧推力系数组成的双线性攻角决策函数,以最小航线偏离角为优化目标,利用粒子群算法求解适用于该航线的最优权重因子,从而得到在不同相对风向角下的最优攻角,既实现风帆助推船舶航行,又不依赖操舵而避免船舶偏离航向。与传统基于最大助推力法的攻角策略相比较,在相同航行时间内,航向纵向位移略有提升,侧向位移和航线偏离角大幅减小,在相对风向角波动时攻角变化较平缓,有利于风帆操纵。本文研究可为提高风帆助航船的能效提供参考。
The decision on wind sail angle is crucial for effectively harnessing wind energy in wind-assisted ships.During ship navigation,the wind sail generates both thrust and lateral thrust,causing ship yawing and reduced energy efficiency.To address this problem,this paper introduced a lateral thrust weight factor and established a bilinear angle decision function composed of the thrust coefficient and the lateral thrust coefficient.The function aimed to minimize the deviation angle of the optimal course and utilized the particle swarm optimization algorithm to solve for the optimal weight factor applicable to the specific route.This approach enables achieving optimal sail angles under different relative wind directions,allowing for wind-assisted ship navigation without relying on steering and avoiding course deviation.Compared to the traditional angle strategy based on the maximum thrust method,the proposed approach results in slight improvement in heading longitudinal displacement within the same navigation time,substantial reduction in sideways displacement and course deviation angle,and smoother angle variations during fluctuations in relative wind direction.These findings are beneficial for wind sail manipulation.This research provides insights to enhance the energy efficiency of wind-assisted ships.
作者
林浩安
陈俐
LIN Haoan;CHEN Li(Ocean Intelligence Laboratory,School of Naval Architecture,Ocean&Civil Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;State Key Laboratory of Ocean Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)
出处
《海洋工程装备与技术》
2024年第1期1-9,共9页
Ocean Engineering Equipment and Technology
基金
国家重点研发计划(2022YFB4300803)
上海交通大学深蓝计划(WH410260401/006)。
关键词
风帆助航船
偏航
攻角策略
优化
wind-assisted ship
course deviation
attack angle strategy
optimization.