Innovative approaches to optimizing Li-Ion battery cooling performance using gas mixtures

被引:0
|
作者
Metallo, Antonio [1 ]
机构
[1] Univ Salerno, Ind Engn Dept, Via Giovanni Paolo 2,132, I-84084 Fisciano, SA, Italy
关键词
Lithium-ion batteries; Thermal management; Battery cooling systems; Heat transfer enhancement; THERMAL MANAGEMENT; HFE-7100; SYSTEM;
D O I
10.1016/j.applthermaleng.2024.124472
中图分类号
O414.1 [热力学];
学科分类号
摘要
This study investigates the critical issue of thermal management in lithium-ion batteries, a vital concern for enhancing battery performance, safety, and longevity. While more complex cooling systems like liquid cooling, phase change materials, and two-phase systems offer superior thermal performance due to their higher heat transfer capabilities, they come with significant drawbacks. These include increased system complexity, higher costs, added weight, and the potential for leaks or other failures that can compromise safety and reliability. Consequently, simpler air-based cooling systems are often preferred in many applications, despite their inherently lower h coefficient. To bridge the performance gap between air and liquid cooling without resorting to complex engineering solutions, this study focuses on enhancing the h coefficient of air-based systems using innovative refrigerant gas mixtures. The use of refrigerant gas mixtures, specifically a blend of R1234ze(E), nitrogen, and neon, as an alternative to traditional cooling methods was explored. The study employed a comprehensive FEM model and experimental validation to evaluate free and forced convection in a slender, vertical cylindrical configuration. To analyze the impact on convective heat transfer, the key parameters CRate, T0 and Tamb were systematically varied. A dimensionless analysis then evaluated how thermodynamic properties influence h coefficient. This analysis led to the derivation of a dimensionless heat transfer function h(rho, Cp, k, mu). The study aimed to significantly improve the efficiency of h by optimizing the gas mixture properties. The "Mixture Study" identifies the optimal refrigerant composition, where a specific mixture alpha of 86 % R1234ze(E), and 14 % neon demonstrated the best balance between heat transfer efficiency and enhanced thermal capacity. The heat transfer coefficient increases by around 65 % during natural convection and by around 80 % during forced convection. The percentage reduction of the thermal difference in temperature reaches approximately 10 % with a maximum of 4 K in natural convection conditions and a maximum of 36.5 % and a reduction of approximately 10 K compared to air cooling alone, effectively maintaining the battery within the optimal operating range of 293.15 K to 333.15 K. Notably, this composition increased the thermal power absorbed by the mixture by over 100 % under the same thermal difference. This research therefore provides valuable insights for developing more effective gas cooling strategies that ultimately enhance the performance, safety, and durability of batteries in various applications. By integrating the benefits of both cooling methods, the study paves the way for innovative thermal management solutions in battery technology.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] Li-ion battery electrolytes
    Xu, Kang
    NATURE ENERGY, 2021, 6 (07) : 763 - 763
  • [22] A perspective on the Li-ion battery
    John B.Goodenough
    Hongcai Gao
    Science China(Chemistry), 2019, 62 (12) : 1555 - 1556
  • [23] A perspective on the Li-ion battery
    John B.Goodenough
    Hongcai Gao
    Science China(Chemistry), 2019, (12) : 1555 - 1556
  • [24] A perspective on the Li-ion battery
    Goodenough, John B.
    Gao, Hongcai
    SCIENCE CHINA-CHEMISTRY, 2019, 62 (12) : 1555 - 1556
  • [25] Parameter Estimation of an Electrochemical Li-ion Battery Model Using Innovative Global Harmony Search
    Chun, Huiyong
    Han, Soohee
    PROCEEDINGS OF TENCON 2018 - 2018 IEEE REGION 10 CONFERENCE, 2018, : 0132 - 0137
  • [26] Graphene/Li-ion battery
    Kheirabadi, Narjes
    Shafiekhani, Azizollah
    JOURNAL OF APPLIED PHYSICS, 2012, 112 (12)
  • [27] Li-ion battery electrolytes
    Kang Xu
    Nature Energy, 2021, 6 : 763 - 763
  • [28] Li-ion Battery Fault Detection in Large Packs Using Force and Gas Sensors
    Cai, Ting
    Mohtat, Peyman
    Stefanopoulou, Anna G.
    Siegel, Jason B.
    IFAC PAPERSONLINE, 2020, 53 (02): : 12491 - 12496
  • [29] ON SOME MODEL REDUCTION APPROACHES FOR SIMULATIONS OF PROCESSES IN LI-ION BATTERY
    Iliev, Oleg
    Latz, Arnulf
    Zausch, Jochen
    Zhang, Shiquan
    ALGORITMY 2012, 2012, : 161 - 171
  • [30] Numerical investigation on cooling performance of Li-ion battery thermal management system at high galvanostatic discharge
    Jilte, R. D.
    Kumar, Ravinder
    ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH, 2018, 21 (05): : 957 - 969