Online prediction of battery discharge and flight mission assessment for electrical rotorcraft

dc.contributor.advisor Peng Wei
dc.contributor.author Alnaqeb, Abdullah
dc.contributor.department Aerospace Engineering
dc.date 2018-08-11T15:48:14.000
dc.date.accessioned 2020-06-30T03:08:29Z
dc.date.available 2020-06-30T03:08:29Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2017
dc.date.embargo 2001-01-01
dc.date.issued 2017-01-01
dc.description.abstract <p>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.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/16069/
dc.identifier.articleid 7076
dc.identifier.contextkey 11413617
dc.identifier.doi https://doi.org/10.31274/etd-180810-5698
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/16069
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/30252
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/16069/Alnaqeb_iastate_0097M_16980.pdf|||Fri Jan 14 20:54:36 UTC 2022
dc.subject.disciplines Aerospace Engineering
dc.subject.keywords Battery Modeling
dc.subject.keywords eVTOL
dc.subject.keywords Online Prediction
dc.subject.keywords UAS
dc.subject.keywords UTM
dc.title Online prediction of battery discharge and flight mission assessment for electrical rotorcraft
dc.type article
dc.type.genre thesis
dspace.entity.type Publication
relation.isOrgUnitOfPublication 047b23ca-7bd7-4194-b084-c4181d33d95d
thesis.degree.discipline Aerospace Engineering
thesis.degree.level thesis
thesis.degree.name Master of Science
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