Hierarchical model-based predictive controller for a hybrid UAV powertrain

The emerging trend of vehicle electrification is transforming the transportation industry by replacing traditional mechanical and hydraulic components with higher performing, more reliable, efficient electrical components. However, introduction a complex network onboard mobile systems poses significant challenges for control design. A notable challenge coordination multi-domain multi-timescale system dynamics. This article seeks to address this through design validation model predictive controller hybrid unmanned aerial powertrain. extension graph-based modeling framework formulated used multi-physics behavior air vehicle. An extensive procedure performed validated graph develop two strategies: one baseline controller. To coordinate dynamics, leverages hierarchical architecture plan battery state charge bound. strategies are experimentally show that advanced yields improvements in performance reliability metrics while reducing fuel consumption ∼10%.