Optimized Hydrodynamic Design for Autonomous Underwater Vehicles

In this study, the drag coefficient and lift-to-drag ratio variation with angle of attack and velocity are analyzed by numerical simulation of the hydrodynamics of the initial shape of an autonomous underwater vehicle (AUV). Based on this, the response surface method (RSM) and multi-objective genetic algorithm (MOGA) are used to optimize the geometric parameters of the shape, aiming to improve the lift-to-drag ratio and reduce the mass. In the study, a second-order response surface model was constructed to analyze the relationship between the target variables and the structural geometric parameters, and the MOGA algorithm effectively searched for the globally optimal solution. The optimization results show that the lift-to-drag ratio is increased from 0.684 to 0.778 and the mass of the shell is reduced from 26.6 kg to 24.06 kg, which significantly improves the hydrodynamic performance of the AUV. The optimization method not only improves the performance of the AUV, but also provides a valuable reference for its hydrodynamic design, which has a good application prospect.