A novel multivariable coupling optimization method of wind-assisted propulsion system for a large crude carrier

Wind-assisted propulsion systems (WAPSs) are increasingly valued in the shipping sector due to their potential to reduce fuel consumption and greenhouse gas (GHG) emissions. However, optimizing the wing-sail angle of attack alone, without considering the coupled effects with other variables, restricts the potential for maximizing energy efficiency. To address this issue, this paper proposes a novel multivariable coupling optimization method. At its core, the multivariables of route, ship speed, ship trim, and angle of attack are optimized in a coupled manner. First, a relatively accurate mathematical model of the WAPS is established, providing a fine representation of the system dynamics. Subsequently, the optimization problem is carefully formulated to minimize the fuel consumption. To tackle the inherent nonlinearity of this optimization problem, the optimization method that integrates sea condition feature recognition and maximum thrust coefficient strategy with an improved particle swarm optimization algorithm is invented. Finally, the method's superiority is validated using three real-world sailing cases of a large crude carrier. The results showed that as much as 8.60 % of fuel consumption and GHG emissions are reduced. Moreover, insight analysis reveals that in regions with abundant wind resources, coupling optimization can help the wing-sail achieve greater thrust performance.