Energy Management Strategy for Cross-Domain Vehicles Based on Multimodal Sensing under Large Disturbance Conditions

The Cross-Domain Vehicle (CDV) refers to a vehicle that can navigate underwater, on the water surface, and in the air. Also known as Unmanned Aerial-Underwater Vehicle (UAUV) by many researchers. It can enter and leave the water many times during the working process. This paper focuses on the intricate energy management issue of CDVs amidst large disturbances. Multimodal sensing technology is employed to collect comprehensive data from a variety of sensors, including motion, environmental, and energy-related sensors. A Improved Deep Q-Network algorithm is then utilized to optimize the energy distribution strategy. And attempt to address the lack of interpretability in deep learning models when dealing with practical problems. Simulation results demonstrate that this approach can effectively improve the energy utilization rate by 6.6% and reduce the SOC fluctuation of lithium battery 2.6%, thus offering an innovative solution for the energy management of cross-media vehicles.