Temperature-based State of Health estimation for Autonomous Underwater Vehicle Batteries using Machine Learning Algorithms

As the demand for autonomous vehicles for terrestrial transportation increases, there has been continuous research on alternative unmanned transport in the deep-sea region. Autonomous Underwater Vehicles require rechargeable batteries such as Lithium-ion batteries that provide a longer travel time. The performance of the energy storage system of AUV is directly affected by temperature conditions, underwater pressure and ageing due to discharge cycles. As the temperature conditions below surface level vary with 1°C reduction at every 10m, descend, at the seabed, the temperature is around -2°C. Lithium-ion batteries have poor performance at such low-temperature conditions is degraded, reducing the battery's cycle life.