Assessing SOC Estimations via Reverse-Time Kalman for Small Unmanned Aircraft

Manuel R. Arahal, Alfredo Pérez Vega-Leal, Manuel G. Satué () and Sergio Esteban
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Manuel R. Arahal: Department of Systems Engineering and Automation, Universidad de Sevilla, 41092 Seville, Spain
Alfredo Pérez Vega-Leal: Department of Electronic Engineering, Universidad de Sevilla, 41092 Seville, Spain
Manuel G. Satué: Department of Systems Engineering and Automation, Universidad de Sevilla, 41092 Seville, Spain
Sergio Esteban: Department of Aerospace Engineering, Universidad de Sevilla, 41092 Seville, Spain

Energies, 2024, vol. 17, issue 20, 1-12

Abstract: This paper presents a method to validate state of charge (SOC) estimations in batteries for their use in remotely manned aerial vehicles (UAVs). The SOC estimation must provide the mission control with a measure of the available range of the aircraft, which is critical for extended missions such as search and rescue operations. However, the uncertainty about the initial state and depth of discharge during the mission makes the estimation challenging. In order to assess the estimation provided to mission control, an a posteriori re-estimation is performed. This allows for the assessment of estimation methods. A reverse-time Kalman estimator is proposed for this task. Accurate SOC estimations are crucial for optimizing the utilization of multiple UAVs in a collaborative manner, ensuring the efficient use of energy resources and maximizing mission success rates. Experimental results for LiFePO4 batteries are provided, showing the capabilities of the proposal for the assessment of online SOC estimators.

Keywords: battery; Kalman estimator; SOC estimation; UAV (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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