Design, modeling and performance analysis of a deformable double-float wave energy converter for AUVs

Autonomous underwater vehicles (AUVs) are one of the most important means of ocean exploration. However, the restricted energy supply poses a significant challenge to the advancement and practical application of AUVs. Based on the structural characteristics, this paper proposes a novel AUV, which integrates a deformable double-float wave energy converter (WEC), called DFWEC-AUV. The DFWEC empowers the AUV to capture wave energy to supply itself by oscillating double-float form in power generation mode. The structural design, focusing on the deformable float (DeF) and the onboard damping plate (DP), and the working principle, including mode switching and energy capture, are firstly introduced. Then, a double-float dynamic model of DFWEC-AUV oscillating in regular waves is established to reveal the energy capture mechanism in both frequency-domain and time-domain. Finally, the influence of the presence of DP, structural parameters (diameter of DP and deployment angle of DeF) and power take-off (PTO) system damping coefficient on the dynamic response characteristics and energy capture performance is analyzed. In addition, to verify the effectiveness of the performance analysis, a comparative simulation of parameter optimization is carried out under actual wave excitation. The results show that the addition of onboard DP is able to effectively enhance the energy capture performance of DFWEC-AUV, as well as increase the energy capture bandwidth. Moreover, the larger the diameter of the DP is, the greater the performance improvement of DFWEC-AUV is. Conversely, increasing the deployment angle of the DeF does not necessarily lead to better power capture performance. Additionally, it is observed that waves of a particular period are consistently associated with an optimal PTO damping coefficient, which leads to superior power capture performance. In comparative simulation, the energy capture performance of DFWEC-AUV after parameter optimization is increased by 4.7 times.