IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v313y2024ics0360544224034480.html
   My bibliography  Save this article

Data-driven optimization of nano-PCM arrangements for battery thermal management based on Lattice Boltzmann simulation

Author

Listed:
  • Zhang, Liwei
  • Shang, Bichen
  • Sun, Weijie
  • Tao, Yao
  • Li, Xueren
  • Tu, Jiyuan

Abstract

An efficient Battery Thermal Management System (BTMS) is vital for maximizing electric vehicle effectiveness and extending service life, essential for sustainable transportation. This study proposes a novel non-uniform nano-PCM distribution strategy within BTMS to tackle battery overheating challenges and further proposes a multi-objective optimization framework combining Back Propagation Neural Networks (BPNN) and Genetic Algorithm (GA) to achieve optimal design solutions for BTMS. Optimization data is derived from the well-validated Lattice Boltzmann Method (LBM) results across 343 cases. Initial evaluations show that a negative gradient distributed nano-PCM (Type 2) improves melting rate, heat dissipation power, and temperature uniformity by 4.67%, 4.87%, 19%, and 7.0%, respectively. The BPNN-GA optimization framework satisfactorily correlates nanoparticle distribution with four evaluation metrics, achieving R2 values from 0.9469 to 0.9987. Optimization improves melting rate, heat dissipation power, and regional and inter-regional temperature uniformity by 9.13%, 9.94%, 7.77%, and 29.73%, respectively. The BPNN-GA also demonstrates reasonable generalizability for the other two practical case scenarios with improvements in certain criteria up to 49.19%. This study highlights the potential of uneven nano-PCM configurations and the efficiency of the LBM-BPNN-GA framework in achieving superior thermal management for BTMS, which is expected to provide insights for future BTMS designs and implementations.

Suggested Citation

  • Zhang, Liwei & Shang, Bichen & Sun, Weijie & Tao, Yao & Li, Xueren & Tu, Jiyuan, 2024. "Data-driven optimization of nano-PCM arrangements for battery thermal management based on Lattice Boltzmann simulation," Energy, Elsevier, vol. 313(C).
    • Handle: RePEc:eee:energy:v:313:y:2024:i:c:s0360544224034480
    DOI: 10.1016/j.energy.2024.133670
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224034480
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.133670?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 search for a different version of it.

    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:313:y:2024:i:c:s0360544224034480. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.