Real time diagnostics and prognostics of UAV lithium-polymer batteries

Conference paper (2019)

Authors

N. Eleftheroglou Structural Integrity & Composites - Aerospace Engineering
Dimitrios Zarouchas Structural Integrity & Composites - Aerospace Engineering
Theodoros Loutas University of Patras
Sina Sharif Mansouri Luleå University of Technology
George Georgoulas University of Patras
Petros Karvelis Luleå University of Technology
George Nikolakopoulos Luleå University of Technology
R Benedictus Structural Integrity & Composites - Aerospace Engineering
Research Group
Structural Integrity & Composites (Aerospace Engineering) (TU Delft)
Copyright: © 2019 N. Eleftheroglou, D. Zarouchas, Theodoros Loutas, Sina Sharif Mansouri, George Georgoulas, Petros Karvelis, George Nikolakopoulos, R. Benedictus
More Info
expand_more

Published Date

2019

Language

English

Faculty

Aerospace Engineering

Department

Aerospace Structures & Materials

Research Group

Structural Integrity & Composites

Abstract

This paper examines diagnostics and prognostics of Lithium-Polymer (Li-Po) batteries for unmanned aerial vehicles (UAVs). Several discharge voltage histories obtained during actual indoor flights constitute the training data for a data-driven approach, utilizing the Non-Homogenous Hidden Semi Markov model (NHHSMM). NHHSMM is a suitable candidate as it has a rich mathematical structure, which is capable of describing the discharge process of Li-Po batteries and providing diagnostic and prognostic measures. Diagnostics and prognostics in unseen data are obtained and compared with the actual remaining flight time in order to validate the effectiveness of the selected model.