IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v401y2025ipas0306261925013674.html

Development and HIL validation of observer-based monitoring algorithms of battery packs for eVTOL UAV applications

Author

Listed:
  • Suti, Aleksander
  • Budinger, Marc
  • Di Rito, Gianpietro
  • Reysset, Aurélien

Abstract

Battery management systems significantly impact the performance of electric Vertical Take Off and Landing Unmanned Aerial Vehicles (eVTOL UAVs). In UAVs powered by multiple battery packs, optimising energy and power to extend cycle life and flight time requires monitoring of state of charge and temperature with a limited number of sensors. To achieve this, the battery pack electro-thermal model is first identified using a dedicated test and validated with experimental data from a current load profile based on a flight mission simulation of the reference UAV. A comprehensive analysis based on convergence speed, computational burden, and disturbance rejection is then conducted to determine the most suitable monitoring algorithm among three widely used observers: the Luenberger Observer (LO), Extended Kalman Filter Observer (EKFO), and Sliding Mode Observer (SMO). The comparison shows that the LO offers the best balance. To mitigate ageing sensitivity in state of temperature estimation, the observer uses the actual terminal voltage to compute heat generation rather than relying solely on model-predicted voltage. This accounts for resistive degradation and enhances robustness, though severe ageing needs a dedicated state of health estimator. The selected observer is validated in real time through a Hardware in the Loop test.

Suggested Citation

  • Suti, Aleksander & Budinger, Marc & Di Rito, Gianpietro & Reysset, Aurélien, 2025. "Development and HIL validation of observer-based monitoring algorithms of battery packs for eVTOL UAV applications," Applied Energy, Elsevier, vol. 401(PA).
    • Handle: RePEc:eee:appene:v:401:y:2025:i:pa:s0306261925013674
    DOI: 10.1016/j.apenergy.2025.126637
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925013674
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.126637?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Qian, Wei & Li, Wan & Guo, Xiangwei & Wang, Haoyu, 2024. "A switching gain adaptive sliding mode observer for SoC estimation of lithium-ion battery," Energy, Elsevier, vol. 292(C).
    2. Xiaosong Hu & Fengchun Sun & Yuan Zou, 2010. "Estimation of State of Charge of a Lithium-Ion Battery Pack for Electric Vehicles Using an Adaptive Luenberger Observer," Energies, MDPI, vol. 3(9), pages 1-18, September.
    3. Boukoberine, Mohamed Nadir & Zhou, Zhibin & Benbouzid, Mohamed, 2019. "A critical review on unmanned aerial vehicles power supply and energy management: Solutions, strategies, and prospects," Applied Energy, Elsevier, vol. 255(C).
    4. Chen, Xiyu & Li, Qingbo & Shao, Bohan & Dou, Weilin & Lai, Chunyan & Lu, Taolin & Xie, Jingying, 2025. "Accurately estimating internal temperature of lithium-ion batteries based on the distribution of relaxation time and data-driven," Energy, Elsevier, vol. 320(C).
    5. Kailong Liu & Kang Li & Qiao Peng & Yuanjun Guo & Li Zhang, 2018. "Data-Driven Hybrid Internal Temperature Estimation Approach for Battery Thermal Management," Complexity, Hindawi, vol. 2018, pages 1-15, July.
    6. Aleksander Suti & Gianpietro Di Rito & Giuseppe Mattei, 2022. "Development and Experimental Validation of Novel Thevenin-Based Hysteretic Models for Li-Po Battery Packs Employed in Fixed-Wing UAVs," Energies, MDPI, vol. 15(23), pages 1-26, December.
    7. Mengying Chen & Fengling Han & Long Shi & Yong Feng & Chen Xue & Weijie Gao & Jinzheng Xu, 2022. "Sliding Mode Observer for State-of-Charge Estimation Using Hysteresis-Based Li-Ion Battery Model," Energies, MDPI, vol. 15(7), pages 1-14, April.
    8. Galeotti, Matteo & Cinà, Lucio & Giammanco, Corrado & Cordiner, Stefano & Di Carlo, Aldo, 2015. "Performance analysis and SOH (state of health) evaluation of lithium polymer batteries through electrochemical impedance spectroscopy," Energy, Elsevier, vol. 89(C), pages 678-686.
    9. Hwang, Foo Shen & Confrey, Thomas & Reidy, Colin & Picovici, Dorel & Callaghan, Dean & Culliton, David & Nolan, Cathal, 2024. "Review of battery thermal management systems in electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xuezhe Wei & Xueyuan Wang & Haifeng Dai, 2018. "Practical On-Board Measurement of Lithium Ion Battery Impedance Based on Distributed Voltage and Current Sampling," Energies, MDPI, vol. 11(1), pages 1-15, January.
    2. Wang, Yujie & Tian, Jiaqiang & Sun, Zhendong & Wang, Li & Xu, Ruilong & Li, Mince & Chen, Zonghai, 2020. "A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    3. Wu, Chen & Liang, Jiaqi & Wang, Yan & Li, Boliang, 2025. "Online state-of-charge estimation for lithium-ion batteries via a high-degree-of-freedom robust observer with model parameter identification," Energy, Elsevier, vol. 334(C).
    4. Khan, Ayesha & Naqvi, Ijaz Haider & Bhargava, Cherry & Lin, Chun-Pang & Boles, Steven Tyler & Kong, Lingxi & Pecht, Michael, 2025. "Safety and reliability analysis of lithium-ion batteries with real-time health monitoring," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    5. Farmann, Alexander & Waag, Wladislaw & Sauer, Dirk Uwe, 2016. "Application-specific electrical characterization of high power batteries with lithium titanate anodes for electric vehicles," Energy, Elsevier, vol. 112(C), pages 294-306.
    6. Cai, Yishan & Yang, Lin & Deng, Zhongwei & Zhao, Xiaowei & Deng, Hao, 2018. "Online identification of lithium-ion battery state-of-health based on fast wavelet transform and cross D-Markov machine," Energy, Elsevier, vol. 147(C), pages 621-635.
    7. Pranav Nair & Vinay Vakharia & Himanshu Borade & Milind Shah & Vishal Wankhede, 2023. "Predicting Li-Ion Battery Remaining Useful Life: An XDFM-Driven Approach with Explainable AI," Energies, MDPI, vol. 16(15), pages 1-19, July.
    8. Hao Sun & Bo Jiang & Heze You & Bojian Yang & Xueyuan Wang & Xuezhe Wei & Haifeng Dai, 2021. "Quantitative Analysis of Degradation Modes of Lithium-Ion Battery under Different Operating Conditions," Energies, MDPI, vol. 14(2), pages 1-19, January.
    9. Tanim, Tanvir R. & Rahn, Christopher D. & Wang, Chao-Yang, 2015. "State of charge estimation of a lithium ion cell based on a temperature dependent and electrolyte enhanced single particle model," Energy, Elsevier, vol. 80(C), pages 731-739.
    10. Li, Yi & Liu, Kailong & Foley, Aoife M. & Zülke, Alana & Berecibar, Maitane & Nanini-Maury, Elise & Van Mierlo, Joeri & Hoster, Harry E., 2019. "Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    11. Hu, Lin & Hu, Xiaosong & Che, Yunhong & Feng, Fei & Lin, Xianke & Zhang, Zhiyong, 2020. "Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering," Applied Energy, Elsevier, vol. 262(C).
    12. Somayeh Toghyani & Seyed Ali Atyabi & Xin Gao, 2021. "Enhancing the Specific Power of a PEM Fuel Cell Powered UAV with a Novel Bean-Shaped Flow Field," Energies, MDPI, vol. 14(9), pages 1-23, April.
    13. Alessandro Giuliano & Yuandi Wu & John Yawney & Stephen Andrew Gadsden, 2025. "Transformer-Based Transfer Learning for Battery State-of-Health Estimation," Energies, MDPI, vol. 18(20), pages 1-21, October.
    14. Zhang, Chaoyu & Zhang, Chengming & Li, Liyi & Guo, Qingbo, 2021. "Parameter analysis of power system for solar-powered unmanned aerial vehicle," Applied Energy, Elsevier, vol. 295(C).
    15. Liu, Yongjie & Huang, Zhiwu & Wu, Yue & Yan, Lisen & Jiang, Fu & Peng, Jun, 2022. "An online hybrid estimation method for core temperature of Lithium-ion battery with model noise compensation," Applied Energy, Elsevier, vol. 327(C).
    16. Wang, Chengshan & Liu, Yixin & Li, Xialin & Guo, Li & Qiao, Lei & Lu, Hai, 2016. "Energy management system for stand-alone diesel-wind-biomass microgrid with energy storage system," Energy, Elsevier, vol. 97(C), pages 90-104.
    17. Khoshvaght-Aliabadi, Morteza & Ghodrati, Parvaneh & Kang, Yong Tae, 2025. "Developing a novel battery thermal management system utilizing supercritical CO2 as the cooling medium," Applied Energy, Elsevier, vol. 381(C).
    18. Chang, Huawei & Cai, Fengyang & Yu, Xianxian & Duan, Chen & Chan, Siew Hwa & Tu, Zhengkai, 2023. "Experimental study on the thermal management of an open-cathode air-cooled proton exchange membrane fuel cell stack with ultra-thin metal bipolar plates," Energy, Elsevier, vol. 263(PA).
    19. Li, Niansi & Liu, Xiaoyong & Yu, Bendong & Li, Liang & Xu, Jianqiang & Tan, Qiong, 2021. "Study on the environmental adaptability of lithium-ion battery powered UAV under extreme temperature conditions," Energy, Elsevier, vol. 219(C).
    20. Tang, Xiaopeng & Liu, Kailong & Lu, Jingyi & Liu, Boyang & Wang, Xin & Gao, Furong, 2020. "Battery incremental capacity curve extraction by a two-dimensional Luenberger–Gaussian-moving-average filter," Applied Energy, Elsevier, vol. 280(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:401:y:2025:i:pa:s0306261925013674. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.