Towards Cognitive Battery Monitoring on Hybrid VTOL Fixed-Wing sUAS with Maximized Safe Endurance

In this work, we explore developments toward an application of cognitive battery monitoring system (CBMS) using a hybrid vertical takeoff and landing (VTOL) fixed-wing small unmanned aircraft system (sUAS). The CBMS is focused on providing an early warning system for safe landings, given long endurance missions, when the battery's state of charge (SOC) is near critical. The CBMS is comprised of a Digital Twin (DT) model that is behavior matched from a pulsed discharge curve using state-of-the-art battery models and Coulomb counting for SOC estimation. The CBMS was subjected to experimental mission data to determine the average cost of the VTOL landing. The CBMS was back-tested on an experimental mission, such that, during the landing phase, the battery limit surpassed the critical regime. The CBMS estimated the remaining useful life (RUL) and provided an early landing warning recommendation. The RUL-based landing prediction provided a safe margin for initializing the landing sequence. Thus the CBMS can be used as a critical tool for safer long endurance missions with VTOL fixed-wing sUAS.