Genetic Optimization of Propeller-Motor Matching for All-Electric Ships

Electric motors are used in the majority of all-electric ship concepts to drive marine propellers. In spite of significant efforts to optimize the propeller selection, there is still a need for the development of propeller optimization methodologies that take into account the ship's operational requirements and match the propeller to an electric motor. In this paper, we employ an optimization procedure that minimizes the electric motor shaft power with respect to the propeller's design parameters in the Wageningen B-screw series. The optimization uses a differential evolution method to evaluate propeller designs while accounting for imposed limits in cavitation, tip velocity, and mechanical strength. The modeling consists of well-known parametric approaches overall but computational fluid dynamics is used for the still-water resistance instead. The optimization algorithm is exercised on an actual ferryboat. The optimization resulted in a 22% percent improvement in the objective function when comparing the worst configurations of initial and final populations. The longest running time was 2.8 hours in an AMD Ryzen 7 3700×8-Core Processor @ 2200 MHz in which 2964 designs were assessed. Similar propeller designs were found for 7.0 and 7.5 knots, except for the expanded area ratio due to the cavitation limit. Geared drives with reductions of about 1.2 and 1.1 were optimal respectively for 7.0 and 7.5 knots, while open-water propeller efficiencies peaked at nearly 39% and 38%.