IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v401y2025ipbs0306261925012243.html

Battery aging-aware adaptive model predictive control based on coupled semi-empirical electro-thermal and aging models

Author

Listed:
  • Dorronsoro, Xabier
  • de Castro, Ricardo
  • Varela Barreras, Jorge
  • Garayalde, Erik
  • Iraola, Unai

Abstract

This paper presents an aging-rate aware nonlinear model predictive control (MPC) strategy for battery energy storage systems, integrating a semi-empirical, experimentally validated electro-thermal and degradation model to account for both calendar and cycle aging factors, often neglected in conventional energy management approaches. A key contribution is the introduction of a adaptive weighting method that dynamically adjusts the weights of the MPC cost function according to the battery’s aging state, primarily driven by time-dependent degradation factors. This adaptive mechanism improves control decisions across varying prediction horizons, leading to reductions in both battery degradation and total operating costs by up to 262.7 % and 44.51 %, respectively, when compared to a standard MPC.

Suggested Citation

  • Dorronsoro, Xabier & de Castro, Ricardo & Varela Barreras, Jorge & Garayalde, Erik & Iraola, Unai, 2025. "Battery aging-aware adaptive model predictive control based on coupled semi-empirical electro-thermal and aging models," Applied Energy, Elsevier, vol. 401(PB).
    • Handle: RePEc:eee:appene:v:401:y:2025:i:pb:s0306261925012243
    DOI: 10.1016/j.apenergy.2025.126494
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925012243
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.126494?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. de Hoog, Joris & Timmermans, Jean-Marc & Ioan-Stroe, Daniel & Swierczynski, Maciej & Jaguemont, Joris & Goutam, Shovon & Omar, Noshin & Van Mierlo, Joeri & Van Den Bossche, Peter, 2017. "Combined cycling and calendar capacity fade modeling of a Nickel-Manganese-Cobalt Oxide Cell with real-life profile validation," Applied Energy, Elsevier, vol. 200(C), pages 47-61.
    2. Schimpe, Michael & Naumann, Maik & Truong, Nam & Hesse, Holger C. & Santhanagopalan, Shriram & Saxon, Aron & Jossen, Andreas, 2018. "Energy efficiency evaluation of a stationary lithium-ion battery container storage system via electro-thermal modeling and detailed component analysis," Applied Energy, Elsevier, vol. 210(C), pages 211-229.
    3. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2018. "Battery energy storage system size determination in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 109-125.
    4. Zou, Bin & Peng, Jinqing & Li, Sihui & Li, Yi & Yan, Jinyue & Yang, Hongxing, 2022. "Comparative study of the dynamic programming-based and rule-based operation strategies for grid-connected PV-battery systems of office buildings," Applied Energy, Elsevier, vol. 305(C).
    5. Jiang, Li & Li, Yong & Ma, Jianmin & Cao, Yijia & Huang, Chun & Xu, Yong & Chen, Hong & Huang, Yuduo, 2020. "Hybrid charging strategy with adaptive current control of lithium-ion battery for electric vehicles," Renewable Energy, Elsevier, vol. 160(C), pages 1385-1395.
    6. Maheshwari, Arpit & Paterakis, Nikolaos G. & Santarelli, Massimo & Gibescu, Madeleine, 2020. "Optimizing the operation of energy storage using a non-linear lithium-ion battery degradation model," Applied Energy, Elsevier, vol. 261(C).
    7. Jorge Varela Barreras & Ricardo de Castro & Yihao Wan & Tomislav Dragicevic, 2021. "A Consensus Algorithm for Multi-Objective Battery Balancing," Energies, MDPI, vol. 14(14), pages 1-25, July.
    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. Collath, Nils & Cornejo, Martin & Engwerth, Veronika & Hesse, Holger & Jossen, Andreas, 2023. "Increasing the lifetime profitability of battery energy storage systems through aging aware operation," Applied Energy, Elsevier, vol. 348(C).
    2. Bechlenberg, Alva & Luning, Egbert A. & Saltık, M. Bahadır & Szirbik, Nick B. & Jayawardhana, Bayu & Vakis, Antonis I., 2024. "Renewable energy system sizing with power generation and storage functions accounting for its optimized activity on multiple electricity markets," Applied Energy, Elsevier, vol. 360(C).
    3. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2022. "Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    4. Vykhodtsev, Anton V. & Jang, Darren & Wang, Qianpu & Rosehart, William & Zareipour, Hamidreza, 2022. "A review of modelling approaches to characterize lithium-ion battery energy storage systems in techno-economic analyses of power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    5. Hou, Qingchun & Yu, Yanghao & Du, Ershun & He, Hongjie & Zhang, Ning & Kang, Chongqing & Liu, Guojing & Zhu, Huan, 2020. "Embedding scrapping criterion and degradation model in optimal operation of peak-shaving lithium-ion battery energy storage," Applied Energy, Elsevier, vol. 278(C).
    6. Khaleghi, Sahar & Karimi, Danial & Beheshti, S. Hamidreza & Hosen, Md. Sazzad & Behi, Hamidreza & Berecibar, Maitane & Van Mierlo, Joeri, 2021. "Online health diagnosis of lithium-ion batteries based on nonlinear autoregressive neural network," Applied Energy, Elsevier, vol. 282(PA).
    7. Ziad Ragab & Ehsan Pashajavid & Sumedha Rajakaruna, 2024. "Optimal Sizing and Economic Analysis of Community Battery Systems Considering Sensitivity and Uncertainty Factors," Energies, MDPI, vol. 17(18), pages 1-20, September.
    8. 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.
    9. Gao, Datong & Zhao, Bin & Kwan, Trevor Hocksun & Hao, Yong & Pei, Gang, 2022. "The spatial and temporal mismatch phenomenon in solar space heating applications: status and solutions," Applied Energy, Elsevier, vol. 321(C).
    10. 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.
    11. Fernando Andrade & Drielli Peyerl & Claudia A. de Mattos, 2025. "Framework for Investment in Electricity Distribution to Enable Energy Transition," Energies, MDPI, vol. 18(3), pages 1-15, February.
    12. Parlikar, Anupam & Truong, Cong Nam & Jossen, Andreas & Hesse, Holger, 2021. "The carbon footprint of island grids with lithium-ion battery systems: An analysis based on levelized emissions of energy supply," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    13. Parlikar, Anupam & Schott, Maximilian & Godse, Ketaki & Kucevic, Daniel & Jossen, Andreas & Hesse, Holger, 2023. "High-power electric vehicle charging: Low-carbon grid integration pathways with stationary lithium-ion battery systems and renewable generation," Applied Energy, Elsevier, vol. 333(C).
    14. Yazhou Zhao & Xiangxi Qin & Xiangyu Shi, 2022. "A Comprehensive Evaluation Model on Optimal Operational Schedules for Battery Energy Storage System by Maximizing Self-Consumption Strategy and Genetic Algorithm," Sustainability, MDPI, vol. 14(14), pages 1-34, July.
    15. Svetlana Drobyazko & Suparna Wijaya & Pavel Blecharz & Sergii Bogachov & Milyausha Pinskaya, 2021. "Modeling of Prospects for the Development of Regional Renewable Energy," Energies, MDPI, vol. 14(8), pages 1-17, April.
    16. Calise, Francesco & Cappiello, Francesco Liberato & Dentice d’Accadia, Massimo & Vicidomini, Maria, 2020. "Dynamic modelling and thermoeconomic analysis of micro wind turbines and building integrated photovoltaic panels," Renewable Energy, Elsevier, vol. 160(C), pages 633-652.
    17. Jagdesh Kumar & Chethan Parthasarathy & Mikko Västi & Hannu Laaksonen & Miadreza Shafie-Khah & Kimmo Kauhaniemi, 2020. "Sizing and Allocation of Battery Energy Storage Systems in Åland Islands for Large-Scale Integration of Renewables and Electric Ferry Charging Stations," Energies, MDPI, vol. 13(2), pages 1-23, January.
    18. Chen, Wei-Hsin & Wang, Chi-Ming & Lee, Da-Sheng & Kwon, Eilhann E. & Ashokkumar, Veeramuthu & Culaba, Alvin B., 2022. "Optimization design by evolutionary computation for minimizing thermal stress of a thermoelectric generator with varied numbers of square pin fins," Applied Energy, Elsevier, vol. 314(C).
    19. Ma, Jian & Xu, Shu & Shang, Pengchao & ding, Yu & Qin, Weili & Cheng, Yujie & Lu, Chen & Su, Yuzhuan & Chong, Jin & Jin, Haizu & Lin, Yongshou, 2020. "Cycle life test optimization for different Li-ion power battery formulations using a hybrid remaining-useful-life prediction method," Applied Energy, Elsevier, vol. 262(C).
    20. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2022. "Forecasting error processing techniques and frequency domain decomposition for forecasting error compensation and renewable energy firming in hybrid systems," Applied Energy, Elsevier, vol. 313(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:pb:s0306261925012243. 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.