Dynamic Analysis of a Series Hybrid–Electric Powertrain for an Unmanned Aerial Vehicle

Abstract

Hybrid–electric powertrains offer the potential for performance improvements in unmanned aerial systems. However, for small unmanned aerial systems, potential gains in range and endurance can depend significantly on the aircraft flight profile and powertrain control logic. Subsequently, these impact the performance of individual powertrain components. This study uses dynamic simulations of an unmanned aerial system (UAS) with different powertrain control logic approaches to evaluate the performance of a series hybrid–electric powertrain. Component models generated using lookup table approaches and model parameterization are combined to generate a dynamic system model of the unmanned aerial system. The performance of the powertrain is evaluated for three representative mission profiles. Fuel consumption and battery state of charge form two metrics that are used to evaluate the performance of a baseline controller against an ideal operating line strategy. The ideal operating line strategy, which uses a performance map obtained by engine characterization on a specialized dynamometer, produces an average fuel economy improvement ranging from 0.5–2.0 g/km for a 30-min-long mission profile. The study demonstrates the need to consider a dynamic analysis aided by detailed component performance maps and a robust control strategy in evaluating hybridization approaches for UAS powertrains.