This paper proposes a bio-inspired hull shape (BHS) for AUV by studying and modeling the body shape of humpback whales. Among factors affecting hydrodynamic characteristics, this paper considers both the hull drag and displacement volume to optimize the BHS, which profitably improve the space utilization and voyage of the AUV. The optimization is conducted by a surrogate model using response surface methodology (RSM), during which the translational propagation Latin hypercube design (TPLHD) is adopted to obtain sampling points. In order to verify the optimization results of BHS, the drag computations for BHS and eight typical hull shapes of existing typical or bionic AUVs are performed for comparison under conditions of similar volume, wet surface area, body length and attachments. A scaled-down model of BHS with attachments is then designed, manufactured and carried out a towing tank test. The drag measured in the towing tank test is basically the same as the simulation result, with the average relative error of 3.68% at 4m/s. The result of the shape optimization performed with the RSM is effective. Furthermore, the proposed BHS is highly suitable for underwater vehicles with requirements for longer distance, higher speed or better sensor carrying capacity.

本文通过对座头鲸的体型进行研究和建模，提出了一种仿生的 AUV 船体形状 (BHS)。在影响水动力特性的因素中，本文同时考虑了船体阻力和排水量来优化BHS，从而有利地提高了AUV的空间利用率和航程。优化采用响应面法（RSM）的代理模型进行，采用平移传播拉丁超立方设计（TPLHD）获取采样点。为了验证BHS的优化结果，在体积、湿表面积、体长和附件相似的条件下，对BHS和现有典型或仿生AUV的八种典型船体形状进行了阻力计算，以进行比较。然后设计了一个带附件的 BHS 缩小模型，制造并进行了拖曳水槽试验。拖曳水池试验测得的阻力与仿真结果基本一致，4m/s时的平均相对误差为3.68%。使用 RSM 执行的形状优化的结果是有效的。此外，所提出的 BHS 非常适合需要更长距离、更高速度或更好传感器承载能力的水下航行器。