Date of Award
Master of Science
In recent concept development and research effort on Unmanned Arial System (UAS) Traffic Management (UTM) and urban on demand mobility (ODM), electric Vertical Take-off and Landing (eVTOL) operations for cargo delivery and passenger transportation need to constantly check if their mission can be successfully completed given the current battery power supply. This onboard or ground-based mission evaluation algorithm is necessary because (1) eVTOL aircraft run on limited battery power; and (2) eVTOL aircraft are usually light weighted so they are subject to wind uncertainties in low-altitude airspace. In this work, the plan is to create an equivalent circuit model (ECM) that best represents the battery pack of a UAS, and then use flight testing to validate the accuracy of that model. Additionally, the ECM will be used to predict the UAS’s ability to complete a specific flight plan successfully. The expected significance of this research is to provide an online framework to constantly monitor and predict battery behavior for mission assessment, which is critical for low-altitude eVTOL operations.
Alnaqeb, Abdullah, "Online prediction of battery discharge and flight mission assessment for electrical rotorcraft" (2017). Graduate Theses and Dissertations. 16069.