Prediction of Lithium-Ion Battery Capacity in UAVs

• Published in: 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT) pp. 1865 - 1869
• Main Authors: Costa, Erick F., Souza, Darielson A., Pinto, Vandilberto P., Araujo, Miqueias S., Peixoto, Artur M., da Costa, Erivaldo P.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-04-2019
• Subjects: Artificial neural networks; Batteries; Degradation; Discharges (electric); ELM ANN; Kalman Filter; Kalman filters; Least Squares; Lithium Ion batteries; Mathematical model; Monitoring; UAVs
• DOI: 10.1109/CoDIT.2019.8820714
• EISSN: 2576-3555

This article proposes a research on degradation of lithium-ion batteries. The life of these batteries can be measured by monitoring capacity degradation. A dataset made available by NASA for the present study was used. Also, 3 methods were used to predict the failure. The methods were Non-recursive Least Squares, a Kalman Filter and an ELM neural network with a very simple architecture, but the results achieved good results and can be compared to other more robust algorithms.