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

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.

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Publication Details

Journal
Energies
Published
2024-10-17
DOI
https://doi.org/10.3390/en17205161
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Manuel G. Satué, Sergio Esteban, Manuel R. Arahal, A. Pérez Vega-Leal
Energies
Fault Detection and Control Systems
article

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

Manuel G. Satué, Sergio Esteban, Manuel R. Arahal, A. Pérez Vega-Leal
article en

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.

EnergiesVol. 17(20)
Universidad de Sevilla (ES)
Agencia Estatal de Investigación
Openalex Percentile: Top 79%
Fault Detection and Control Systems
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