An Analytical Model for Time-Dependent Battery Level Distribution for UAVs

Ayda Baheri Eslami; Mehmet Akif Yazici

doi:10.1007/978-3-031-92143-8_13

An Analytical Model for Time-Dependent Battery Level Distribution for UAVs

Ayda Baheri Eslami
, Mehmet Akif Yazici^*

^*Corresponding author for this work

Informatics Institute

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Unmanned aerial vehicles (UAVs) have a wide range of uses, including surveillance, military, disaster relief, communications, smart agriculture, and delivery. They can also be equipped with various sensors to act as sensor nodes in a sensor network to perform data collection tasks. The battery level of a UAV is of utmost importance when the trajectory of the UAV is planned. The probability distribution of the battery level of a UAV after a certain time in a stochastic setting, possibly involving solar energy harvesting, can be used in trajectory optimization. In this chapter, we present a Markov fluid queue-based analytical model for the transient distribution of the battery level. We demonstrate that the proposed method is accurate in comparison to simulations, and we present a gallery of numerical results illustrating various scenarios.

Original language	English
Title of host publication	8th EAI International Conference on Robotic Sensor Networks - EAI ROSENET 2024
Editors	Behçet Ugur Töreyin, Hatice Köse, Nizamettin Aydin, Ömer Melih Gül, Seifedine Nimer Kadry
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	183-198
Number of pages	16
ISBN (Print)	9783031921421
DOIs	https://doi.org/10.1007/978-3-031-92143-8_13
Publication status	Published - 2026
Event	8th EAI International Conference on Robotics and Networks, EAI ROSENET 2024 - Crete, Greece Duration: 3 Sept 2024 → 5 Sept 2024

Publication series

Name	EAI/Springer Innovations in Communication and Computing
ISSN (Print)	2522-8595
ISSN (Electronic)	2522-8609

Conference

Conference	8th EAI International Conference on Robotics and Networks, EAI ROSENET 2024
Country/Territory	Greece
City	Crete
Period	3/09/24 → 5/09/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Keywords

Battery model
Energy harvesting
Markov fluid queue
Unmanned aerial vehicle

Access to Document

10.1007/978-3-031-92143-8_13

Cite this

Eslami, A. B., & Yazici, M. A. (2026). An Analytical Model for Time-Dependent Battery Level Distribution for UAVs. In B. U. Töreyin, H. Köse, N. Aydin, Ö. Melih Gül, & S. Nimer Kadry (Eds.), 8th EAI International Conference on Robotic Sensor Networks - EAI ROSENET 2024 (pp. 183-198). (EAI/Springer Innovations in Communication and Computing). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-92143-8_13

Eslami, Ayda Baheri ; Yazici, Mehmet Akif. / An Analytical Model for Time-Dependent Battery Level Distribution for UAVs. 8th EAI International Conference on Robotic Sensor Networks - EAI ROSENET 2024. editor / Behçet Ugur Töreyin ; Hatice Köse ; Nizamettin Aydin ; Ömer Melih Gül ; Seifedine Nimer Kadry. Springer Science and Business Media Deutschland GmbH, 2026. pp. 183-198 (EAI/Springer Innovations in Communication and Computing).

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Eslami, AB & Yazici, MA 2026, An Analytical Model for Time-Dependent Battery Level Distribution for UAVs. in BU Töreyin, H Köse, N Aydin, Ö Melih Gül & S Nimer Kadry (eds), 8th EAI International Conference on Robotic Sensor Networks - EAI ROSENET 2024. EAI/Springer Innovations in Communication and Computing, Springer Science and Business Media Deutschland GmbH, pp. 183-198, 8th EAI International Conference on Robotics and Networks, EAI ROSENET 2024, Crete, Greece, 3/09/24. https://doi.org/10.1007/978-3-031-92143-8_13

An Analytical Model for Time-Dependent Battery Level Distribution for UAVs. / Eslami, Ayda Baheri; Yazici, Mehmet Akif.
8th EAI International Conference on Robotic Sensor Networks - EAI ROSENET 2024. ed. / Behçet Ugur Töreyin; Hatice Köse; Nizamettin Aydin; Ömer Melih Gül; Seifedine Nimer Kadry. Springer Science and Business Media Deutschland GmbH, 2026. p. 183-198 (EAI/Springer Innovations in Communication and Computing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An Analytical Model for Time-Dependent Battery Level Distribution for UAVs

AU - Eslami, Ayda Baheri

AU - Yazici, Mehmet Akif

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

PY - 2026

Y1 - 2026

N2 - Unmanned aerial vehicles (UAVs) have a wide range of uses, including surveillance, military, disaster relief, communications, smart agriculture, and delivery. They can also be equipped with various sensors to act as sensor nodes in a sensor network to perform data collection tasks. The battery level of a UAV is of utmost importance when the trajectory of the UAV is planned. The probability distribution of the battery level of a UAV after a certain time in a stochastic setting, possibly involving solar energy harvesting, can be used in trajectory optimization. In this chapter, we present a Markov fluid queue-based analytical model for the transient distribution of the battery level. We demonstrate that the proposed method is accurate in comparison to simulations, and we present a gallery of numerical results illustrating various scenarios.

AB - Unmanned aerial vehicles (UAVs) have a wide range of uses, including surveillance, military, disaster relief, communications, smart agriculture, and delivery. They can also be equipped with various sensors to act as sensor nodes in a sensor network to perform data collection tasks. The battery level of a UAV is of utmost importance when the trajectory of the UAV is planned. The probability distribution of the battery level of a UAV after a certain time in a stochastic setting, possibly involving solar energy harvesting, can be used in trajectory optimization. In this chapter, we present a Markov fluid queue-based analytical model for the transient distribution of the battery level. We demonstrate that the proposed method is accurate in comparison to simulations, and we present a gallery of numerical results illustrating various scenarios.

KW - Battery model

KW - Energy harvesting

KW - Markov fluid queue

KW - Unmanned aerial vehicle

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DO - 10.1007/978-3-031-92143-8_13

M3 - Conference contribution

AN - SCOPUS:105025038030

SN - 9783031921421

T3 - EAI/Springer Innovations in Communication and Computing

SP - 183

EP - 198

BT - 8th EAI International Conference on Robotic Sensor Networks - EAI ROSENET 2024

A2 - Töreyin, Behçet Ugur

A2 - Köse, Hatice

A2 - Aydin, Nizamettin

A2 - Melih Gül, Ömer

A2 - Nimer Kadry, Seifedine

PB - Springer Science and Business Media Deutschland GmbH

T2 - 8th EAI International Conference on Robotics and Networks, EAI ROSENET 2024

Y2 - 3 September 2024 through 5 September 2024

ER -

Eslami AB, Yazici MA. An Analytical Model for Time-Dependent Battery Level Distribution for UAVs. In Töreyin BU, Köse H, Aydin N, Melih Gül Ö, Nimer Kadry S, editors, 8th EAI International Conference on Robotic Sensor Networks - EAI ROSENET 2024. Springer Science and Business Media Deutschland GmbH. 2026. p. 183-198. (EAI/Springer Innovations in Communication and Computing). doi: 10.1007/978-3-031-92143-8_13

An Analytical Model for Time-Dependent Battery Level Distribution for UAVs

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Keywords

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