IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v322y2025ics0360544225011983.html
   My bibliography  Save this article

Optimal control of cooling performance using an active disturbance rejection controller for lithium-ion battery packs

Author

Listed:
  • Li, Dailin
  • An, Zhiguo
  • Zhou, Yongfeng
  • Zhang, Jianping
  • Gao, Zhengyuan

Abstract

The development of electric vehicles (EVs) contributes to reducing air pollution and the consumption of traditional fossil fuels. However, the battery thermal management system (BTMS) still faces challenges, such as slow cooling rates and poor environmental adaptability during high-rate charging and discharging. An Active Disturbance Rejection Control (ADRC) method is proposed to address these issues. This study investigates the cooling performance of a bidirectional convection cooling channel structure under constant discharge conditions, severe current driving conditions, and high-temperature environments. The results indicate that, at discharge rates of 0.5C, 1C, and 2C, ADRC exhibited the ideal temperature uniformity with maximum temperature differences of merely 1.3 °C, 1.33 °C, and 1.36 °C, respectively. Under NEDC and US06 driving conditions, the cooling rate of ADRC was increased by up to 54.5 % and 76.5 %, respectively. Furthermore, under US06 driving conditions characterized by high speeds and aggressive acceleration at an ambient temperature of 50 °C, ADRC demonstrated superior thermal management stability, with only one instance exceeding the target temperature threshold. The application of ADRC algorithms is anticipated to have significant implications in the EV field by ensuring precise temperature control, enabling the battery to operate in an optimal state, extending its service life, and enhancing the robustness and safety of the system under complex environmental conditions.

Suggested Citation

  • Li, Dailin & An, Zhiguo & Zhou, Yongfeng & Zhang, Jianping & Gao, Zhengyuan, 2025. "Optimal control of cooling performance using an active disturbance rejection controller for lithium-ion battery packs," Energy, Elsevier, vol. 322(C).
  • Handle: RePEc:eee:energy:v:322:y:2025:i:c:s0360544225011983
    DOI: 10.1016/j.energy.2025.135556
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225011983
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.135556?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. Nasiri, Mahdieh & Hadim, Hamid, 2024. "Advances in battery thermal management: Current landscape and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 200(C).
    2. Xie, Jiahang & Yang, Rufan & Gooi, Hoay Beng & Nguyen, Hung Dinh, 2023. "PID-based CNN-LSTM for accuracy-boosted virtual sensor in battery thermal management system," Applied Energy, Elsevier, vol. 331(C).
    3. Wen, Jianping & Zhao, Dan & Zhang, Chuanwei, 2020. "An overview of electricity powered vehicles: Lithium-ion battery energy storage density and energy conversion efficiency," Renewable Energy, Elsevier, vol. 162(C), pages 1629-1648.
    4. D. M. Davies & M. G. Verde & O. Mnyshenko & Y. R. Chen & R. Rajeev & Y. S. Meng & G. Elliott, 2019. "Combined economic and technological evaluation of battery energy storage for grid applications," Nature Energy, Nature, vol. 4(1), pages 42-50, January.
    5. Weng, Jingwen & Xiao, Changren & Yang, Xiaoqing & Ouyang, Dongxu & Chen, Mingyi & Zhang, Guoqing & Lee Waiming, Eric & Kit Yuen, Richard Kwowk & Wang, Jian, 2022. "An energy-saving battery thermal management strategy coupling tubular phase-change-material with dynamic liquid cooling under different ambient temperatures," Renewable Energy, Elsevier, vol. 195(C), pages 918-930.
    6. Gharehghani, Ayat & Rabiei, Moeed & Mehranfar, Sadegh & Saeedipour, Soheil & Mahmoudzadeh Andwari, Amin & García, Antonio & Reche, Carlos Mico, 2024. "Progress in battery thermal management systems technologies for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 202(C).
    7. Liu, Zhangmiaoge & Liu, Zhouxiao & Liu, Jianzhao & Wang, Ning, 2023. "Thermal management with fast temperature convergence based on optimized fuzzy PID algorithm for electric vehicle battery," Applied Energy, Elsevier, vol. 352(C).
    8. Guo, Rong & Sun, Ziyi & Luo, Maohui, 2024. "Energy-efficient battery thermal management strategy for range extended electric vehicles based on model predictive control and dynamic programming," Energy, Elsevier, vol. 307(C).
    9. Rajib Mahamud & Chanwoo Park, 2022. "Theory and Practices of Li-Ion Battery Thermal Management for Electric and Hybrid Electric Vehicles," Energies, MDPI, vol. 15(11), pages 1-45, May.
    10. Shuai Mao & Zhoujian An & Xiaoze Du & Tianlu Shi & Dong Zhang, 2022. "Coupling Analysis on the Thermophysical Parameters and the Performance of Liquid Cooling-Based Thermal Management System for Lithium-Ion Batteries," Energies, MDPI, vol. 15(19), pages 1-15, September.
    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. Yang, Rufan & Nguyen, Hung Dinh, 2025. "Temperature distribution learning of Li-ion batteries using knowledge distillation and self-adaptive models," Applied Energy, Elsevier, vol. 382(C).
    2. Wang, Chuang & Liu, Qixing & Wang, Zhiqiang & Cheng, Xingxing, 2025. "A review of power battery cooling technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 213(C).
    3. Schauf, Magnus & Schwenen, Sebastian, 2023. "System price dynamics for battery storage," Energy Policy, Elsevier, vol. 183(C).
    4. Hong, Jichao & Li, Kerui & Liang, Fengwei & Yang, Haixu & Zhang, Chi & Yang, Qianqian & Wang, Jiegang, 2024. "A novel state of health prediction method for battery system in real-world vehicles based on gated recurrent unit neural networks," Energy, Elsevier, vol. 289(C).
    5. Wang, Ji-Xiang & Qian, Jian & Wang, Ni & Zhang, He & Cao, Xiang & Liu, Feifan & Hao, Guanqiu, 2023. "A scalable micro-encapsulated phase change material and liquid metal integrated composite for sustainable data center cooling," Renewable Energy, Elsevier, vol. 213(C), pages 75-85.
    6. Li, Jing & Zuo, Wei & E, Jiaqiang & Zhang, Yuntian & Li, Qingqing & Sun, Ke & Zhou, Kun & Zhang, Guangde, 2022. "Multi-objective optimization of mini U-channel cold plate with SiO2 nanofluid by RSM and NSGA-II," Energy, Elsevier, vol. 242(C).
    7. Wen, Jianping & Chen, Xing & Li, Xianghe & Li, Yikun, 2022. "SOH prediction of lithium battery based on IC curve feature and BP neural network," Energy, Elsevier, vol. 261(PA).
    8. Liu, Wenxue & Hu, Xiaosong & Zhang, Kai & Xie, Yi & He, Jinsong & Song, Ziyou, 2025. "Enabling high-fidelity electrothermal modeling of electric flying car batteries: A physics-data hybrid approach," Applied Energy, Elsevier, vol. 388(C).
    9. Li, Xiaolin & Wang, Jun & Wu, Zhiwei & Cao, Wenxiang & Zhang, Xuesong, 2024. "An energy saving strategy on the composite phase change material and spiral liquid cooling channel for battery thermal management," Renewable Energy, Elsevier, vol. 227(C).
    10. Chen, Dongwen & Li, Yong & Abbas, Zulkarnain & Li, Dehong & Wang, Ruzhu, 2022. "Network flow calculation based on the directional nodal potential method for meshed heating networks," Energy, Elsevier, vol. 243(C).
    11. Hunek, Wojciech P. & Feliks, Tomasz, 2025. "A new set of multivariable predictive control algorithms for time-delayed nonsquare systems of different domains: A minimum-energy examination," Applied Energy, Elsevier, vol. 381(C).
    12. Maria M. Symeonidou & Effrosyni Giama & Agis M. Papadopoulos, 2021. "Life Cycle Assessment for Supporting Dimensioning Battery Storage Systems in Micro-Grids for Residential Applications," Energies, MDPI, vol. 14(19), pages 1-16, September.
    13. Fu, Jianqin & Li, Hao & Sun, Xilei & He, Tingpu & Zhang, Guanjie & Wei, Changhe, 2025. "Multi-physics simulation modeling and energy flow characterization of thermal management system for a sport utility vehicle under high-temperature conditions," Energy, Elsevier, vol. 316(C).
    14. Zhou, Guangzhao & Guo, Zanquan & Sun, Simin & Jin, Qingsheng, 2023. "A CNN-BiGRU-AM neural network for AI applications in shale oil production prediction," Applied Energy, Elsevier, vol. 344(C).
    15. Englberger, Stefan & Abo Gamra, Kareem & Tepe, Benedikt & Schreiber, Michael & Jossen, Andreas & Hesse, Holger, 2021. "Electric vehicle multi-use: Optimizing multiple value streams using mobile storage systems in a vehicle-to-grid context," Applied Energy, Elsevier, vol. 304(C).
    16. Ruixue Liu & Guannan He & Xizhe Wang & Dharik Mallapragada & Hongbo Zhao & Yang Shao-Horn & Benben Jiang, 2024. "A cross-scale framework for evaluating flexibility values of battery and fuel cell electric vehicles," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    17. Sun, Xilei & Fu, Jianqin, 2024. "Experiment investigation for interconnected effects of driving cycle and ambient temperature on bidirectional energy flows in an electric sport utility vehicle," Energy, Elsevier, vol. 300(C).
    18. Mo, Jixiao & Zhang, Guoqing & Zhang, Jiangyun & Mo, Chou & Wang, Bo & Guo, Shuqing & Jiang, Renjun & Liu, Jun & Peng, Kang, 2025. "Effect of cold welding on the inconsistencies and thermal safety of battery modules based on a constructed discharge model," Applied Energy, Elsevier, vol. 377(PC).
    19. Liu, Shujun & Wang, Yao & Liu, Qi & Panchal, Satyam & Zhao, Jiapei & Fowler, Michael & Fraser, Roydon & Yuan, Jinliang, 2024. "Thermal equalization design for the battery energy storage system (BESS) of a fully electric ship," Energy, Elsevier, vol. 312(C).
    20. Hu, Zhuo & Wang, Tao & Cao, Yuwei & Yang, Qing, 2024. "Electric vehicle aggregator as demand dispatch resources: Exploring the impact of real-time market performance on day-ahead market," Energy, Elsevier, vol. 308(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:energy:v:322:y:2025:i:c:s0360544225011983. 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.journals.elsevier.com/energy .

    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.