Generative Design and Optimization of Battery Packs with Active Immersion Cooling

被引:2
|
作者
Liu, Zheng [1 ]
Wu, Jiaxin [1 ]
Fu, Wuchen [2 ]
Kabirazadeh, Pouya [2 ]
Kohtz, Sara [1 ]
Miljkovic, Nenad [2 ]
Li, Yumeng [1 ]
Wang, Pingfeng [1 ]
机构
[1] Univ Illinois, Dept Ind & Enterprise Syst Engn, Urbana, IL 61801 USA
[2] Univ Illinois, Dept Mech Sci & Engn, Urbana, IL USA
基金
美国国家科学基金会;
关键词
Battery management system; Battery active cooling; Design optimization; Machine learning; Generative model;
D O I
10.1109/ITEC55900.2023.10187078
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Among different battery packaging technologies, cell-to-pack is a widely used method to reduce the cost and increase the volumetric density of battery packs. Unlike the traditional cell-to-module technology, it requires more robust management to keep the temperature uniformity of all cells within a desirable range to ensure good pack performances. Besides active cooling controls, the layout of cells within the battery pack plays an important role in cooling performances, and thus needs to be optimized for lower cooling costs considering the geometry limitations of the pack. This paper presents the layout optimization of the battery pack with active immersion cooling for the 21700 cylindrical battery pack under harsh loading conditions. Based on the experiment testing, the finite element model with electric and thermal couplings has been built in COMSOL Multiphysics. To reduce the high computational cost, a data-driven generative design method based on variational autoencoder has been developed, which could autonomously mine useful properties from the data set of existing battery layout designs and performance metrics. With the generative design method, candidate designs that optimize the layout decisions can be identified. Based on the computational studies, the cooling cost can be lowered by more than 90% with the identified optimal layout design.
引用
收藏
页数:5
相关论文
共 50 条
  • [21] Design and Optimization of Cooling Plate for Battery Module of an Electric Vehicle
    Ye, Ben
    Rubel, Md Rashedul Haque
    Li, Hongjun
    APPLIED SCIENCES-BASEL, 2019, 9 (04):
  • [22] Modular Active Charge Balancing for Scalable Battery Packs
    Narayanaswamy, Swaminathan
    Kauer, Matthias
    Steinhorst, Sebastian
    Lukasiewycz, Martin
    Chakraborty, Samarjit
    IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2017, 25 (03) : 974 - 987
  • [23] Synthesis of Active Cell Balancing Architectures for Battery Packs
    Lukasiewycz, Martin
    Kauer, Matthias
    Steinhorst, Sebastian
    IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2016, 35 (11) : 1876 - 1889
  • [24] Optimal control of cooling performance using an active disturbance rejection controller for lithium-ion battery packs
    Li, Dailin
    An, Zhiguo
    Zhou, Yongfeng
    Zhang, Jianping
    Gao, Zhengyuan
    ENERGY, 2025, 322
  • [25] A liquid cooling plate based on topology optimization and bionics simplified design for battery cooling
    Ren, Jisheng
    Qiu, Xianghui
    Wang, Shuangfeng
    JOURNAL OF ENERGY STORAGE, 2024, 102
  • [26] Dense Server Design for Immersion Cooling
    Kodnongbua, Milin
    Englhardt, Zachary
    Bianchini, Ricardo
    Fonseca, Rodrigo
    Lebeck, Alvin
    Berger, Daniel S.
    Iyer, Vikram
    Kazhamiaka, Fiodar
    Schulz, Adriana
    ACM Transactions on Graphics, 2024, 43 (06):
  • [27] Design optimization of electric vehicle battery cooling plates for thermal performance
    Jarrett, Anthony
    Kim, Il Yong
    JOURNAL OF POWER SOURCES, 2011, 196 (23) : 10359 - 10368
  • [28] The Cell Cooling Coefficient as a design tool to optimise thermal management of lithium-ion cells in battery packs
    Hales, Alastair
    Prosser, Ryan
    Diaz, Laura Bravo
    White, Gavin
    Patel, Yatish
    Offer, Gregory
    ETRANSPORTATION, 2020, 6
  • [29] Optimization of Lithium-ion battery thermal performance using dielectric fluid immersion cooling technique
    Kumaran, A. Thiru
    Hemavathi, S.
    PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2024, 189 : 768 - 781
  • [30] Modeling liquid immersion-cooling battery thermal management system and optimization via machine learning
    Ahmad, Shakeel
    Liu, Yanhui
    Khan, Shahid Ali
    Shah, Syed Waqar Ali
    Huang, Xinyan
    INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER, 2024, 158