Design Optimization and Experimental Validation of a Pendulum-Based Wave Energy Converter for Autonomous Ocean Drones

Authors

  • Arsh Khan
  • Evan Kuo
  • Elaf Alahdal
  • Nilesh Kothari
  • Mikin Patel
  • Reza Alam UC Berkeley

DOI:

https://doi.org/10.36688/ewtec-2025-1141

Keywords:

wave energy converter, Surface Autonomous Drone, Ocean Monitoring

Abstract

We have designed, developed and deployed autonomous ocean drones for long-duration ocean monitoring, but their operational endurance is constrained by power limitations. While renewable energy sources such as solar and wind power are available, their intermittent nature poses challenges for continuous operation. In contrast, wave energy is a persistent and abundant resource that can be leveraged to enhance the energy autonomy of ocean drones. This study presents the design optimization and experimental validation of a pendulum-based wave energy converter (WEC) integrated into the keel of an autonomous ocean drone. The proposed WEC, housed in the keel and measuring 24 inches in length, harnesses the drone’s natural wave-induced motion to generate electrical power, reducing reliance on stored battery energy and extending mission duration. A prototype system is fabricated and tested in controlled wave tank experiments, where power output, energy conversion efficiency, and impact on drone stability are analyzed. The experimental results are compared with theoretical predictions to validate the model and refine the system’s performance. Following the wave tank experiments, the WEC will be integrated into operational autonomous drones deployed in San Francisco Bay to validate its real-world performance. This work demonstrates the feasibility of utilizing pendulum-based wave energy harvesting to power autonomous ocean drones, contributing to the development of self-sustaining platforms for ocean monitoring, climate research, and offshore surveillance.

Published

2025-09-08

How to Cite

[1]
“Design Optimization and Experimental Validation of a Pendulum-Based Wave Energy Converter for Autonomous Ocean Drones”, Proc. EWTEC, vol. 16, Sep. 2025, doi: 10.36688/ewtec-2025-1141.