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Immersion cooling, where cooling fluid flows in direct contact with the Li-ion cell, provides superior temperature control compared to other battery thermal management systems (BTMSs). Although the temperature rise during charging/discharging is low for immersion cooling, the inherent complexity of the cooling approach makes it difficult to predict and control performance. In general, numerical approaches are required to design and analyze immersion cooled BTMS configurations. For accurate results, models must fully couple the electrochemical and thermal-fluid physics solvers. However, such a numerical approach is computationally expensive and may not be feasible, in particular, for large BTMS systems. In the present study, we develop a computationally-efficient approach with coupled electrochemical and thermo-fluid physics to study immersion cooling based BTMSs. The core strategy is to use either analytical expressions or combination of analytical and numerical solutions for all the governing physics. Depending on the discharge rate and on the final design objective, different levels of simplification are leveraged to analyze the thermal and electrochemical response of the system. For the present analysis, we consider discharging of a cylindrical nickel manganese cobalt oxide (NCM) 18650 cell that is immersed in a cooling fluid stream. Different combinations of mass flow rates and fluids (deionized water, mineral oil, and air) are considered to evaluate performance. For every configuration, we first analyze the system with a fully-coupled fully numerical model and this data serves as the reference to judge the accuracy of the newly developed models. Note that the parameters used in the electrochemical models (such as electrolyte and electrode properties, as well as the reaction rates) are the same for the fully-numerical and the quasi-analytical models allowing direct comparison of the results. To isolate the impact of using the simplified models for the electrochemical aspects, a second set of comparison data is generated using the analytical electrochemical model in conjunction with the full-scale numerical thermo-fluid model. The analytical models rely on calculating a heat transfer coefficient to include the impact of the fluid flow and the heat transfer coefficient can be estimated from correlations or from the fully-coupled fully-numerical models. In general, for air-cooled configuration, the thermal and electrochemical performance (i.e., trend and magnitude of temperature rise and cell potential) of the quasi-analytical models matches the fully-coupled full-scale numerical model. But for other fluids, the results deviate from the baseline fully-coupled fully-numerical models unless the numerical fluid models are used to estimate the evolution of heat transfer coefficient throughout the discharging process. Specifically, a small number of fully-coupled fully-numerical simulations are leveraged to train the quasi-analytical model (based on a particular geometry) for rapid analysis and optimization of the BTMS. In summary, the newly developed models including the numerical data-driven learning provide an efficient trade-off between computation cost and accuracy.
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This content will become publicly available on March 1, 2026
Effect of immersion cooling parameters on thermal and electrochemical response of a Li-ion cell
Forced immersion cooling, where a dielectric fluid flows in contact with the cells, is an effective cooling approach for lithium-ion batteries. While previous models demonstrated effectiveness, they generally focused on thermal-fluid aspects and often neglected the coupling between temperature, cell potential, and heat generation (in other words, the electrochemistry remained unaffected by cooling conditions). Here, we use a fully coupled modeling approach that solves the detailed electrochemical model (with temperature-dependent properties) in conjunction with the thermal-fluid transport models at each time step. For an 18650 cell, we compare forced immersion cooling (water and mineral oil) to forced air cooling. Improved temperature control with immersion cooling leads to higher heat generation with increased capacity loss: a 3 K temperature rise corresponds to 10% loss, whereas 42 K temperature rise results in 0.4% loss at 5C discharge. Neglecting two-way coupling prohibits accurate analysis of the effectiveness of immersion cooling. Furthermore, the thermal conductivity and heat capacity of the fluid most significantly impact the electrochemical and thermal response. Finally, we define a new metric to compare performance with different flow parameters without computationally-expensive numerical simulations. Overall, this study provides insights that will be useful in understanding and design of immersion-cooled battery systems.
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- Award ID(s):
- 2143043
- PAR ID:
- 10569807
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Journal of Power Sources
- Volume:
- 632
- Issue:
- C
- ISSN:
- 0378-7753
- Page Range / eLocation ID:
- 236285
- Subject(s) / Keyword(s):
- Batteries Lithium-Ion Batteries Thermal Transport Thermo-fluid Models Electrochemistry
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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