Battery Charge Depletion Prediction on an Electric Aircraft

Cuong C. Quach, Brian Bole, Edward Hogge, Sixto Vazquez, Mathew Daigle, Jose Celaya, Adam Weber, and Kai Goebel
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_13_066.pdf3.83 MBOctober 10, 2013 - 9:48am

Validation of prognostic technologies through ground and flight tests is an important step in maturing these novel technologies and deploying them on real-world systems. To this end, a series of flight tests have been conducted using an unmanned electric vehicle during which the motor system batteries were monitored by a prognostic algorithm. The research presented here endeavors to produce and validate a technology for predicting the remaining time until end-ofdischarge of the batteries on an electric aircraft as a function of an expected future flight and online estimates of the charge contained in the batteries. Flight data and flight experiment results are presented along with an assessment of model and algorithm performance

Publication Year: 
2013
Publication Volume: 
4
Publication Control Number: 
066
Page Count: 
10
Submission Keywords: 
Battery discharge prognostics
Electric Aircraft
Kalman Filtering
unmanned aerial vehicle
Submission Topic Areas: 
Model-based methods for fault detection, diagnostics, and prognosis
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