An Online Energy Management System Based on Minimum-Time Speed Planning for Autonomous Underwater Vehicles

Velocity of autonomous underwater vehicles (AUVs) plays a significant role in the energy consumption of these vehicles, as well as their other capabilities, such as localization, maneuverability, and time to complete assigned missions. In this paper, for the first time, an online energy management strategy (EMS) is proposed for AUVs, which enables approaching the target in minimum time by adjusting the sub-optimal speed according to the amount of available energy. In this model-based energy management system, a framework is proposed that its output is the highest forward speed, so that the mission duration is minimized and the stored battery energy is used in the best possible way. In this field, existing efforts are mostly focused on reducing energy consumption, without considering other vehicle capabilities, but this method tries to reduce this gap. First, the architecture of an AUV propulsion is described and modeled, and a nonlinear equation is derived to generate the sub-optimal speed, which simultaneously minimize the amount of energy consumption and the time to reach the target. Then, for online implementation of this algorithm, a framework is proposed that generates the desired speed by using the battery state of charge (SOC), the voltage and the instantaneous Distance to destination. Illustrative simulation examples were conducted in MATLAB/Simulink to demonstrate the validity of the proposed scheme and the hardware in the loop test is conducted to evaluate the computational complexity of algorithm. Finally, experimental results showed the practical effectiveness of the proposed EMS.