DOI:
https://doi.org/10.14483/23448393.22822Published:
2025-11-13Issue:
Vol. 30 No. 3 (2025): September-DecemberSection:
Mechanical EngineeringTwo-Phase Mixture Numerical Study of Nanofluid Flow in a Lithium-Ion Battery Cooling System
Estudio numérico de mezcla bifásica del flujo de nanofluidos en un sistema de enfriamiento para una batería de iones de litio
Keywords:
computational fluid dynamics, lithium-ion battery, cooling, battery thermal management, mixture (en).Keywords:
dinámica de fluidos computacional, batería de iones de litio, refrigeración, nanofluidos, mezcla, gestión térmica de la batería (es).Downloads
Abstract (en)
Context: The cooling performance of a thermal battery plays a critical role in its efficiency, lifespan, and safety. This importance stems from the heat generated during charging and discharging processes. As temperatures rise, key battery characteristics are significantly affected.
Method: Using the ANSYS Fluent computational fluid dynamics software, a 2D numerical simulation was conducted to study the cooling of a lithium-ion battery in the presence of nanofluids. The flow of nanofluids was analyzed using the multiphase mixture model.
Results: It was found that the coolant inlet velocity significantly impacts the module's temperature distribution and the maximum temperature difference, where the temperature differences almost stabilize for inlet velocities exceeding 0.3 m/s. The effect of using nanofluids was studied with three different types of nanoparticles (alumina, copper, and fullerene) dispersed in water as the base fluid. The results show that the temperature difference in the module varies depending on the nature and volume fraction of the nanoparticles. The incorporation of nanofluids leads to a significant reduction in module temperatures. Fullerene nanoparticles were found to exhibit superior cooling performance compared to other nanoparticle types. On the other hand, a nanoparticle volume fraction exceeding 2% yields a nearly uniform temperature distribution within the module, as well as reduced cell temperatures.
Conclusions: Nanofluids have an important effect on battery cooling. Optimizing nanoparticle concentration and flow dynamics can effectively improve thermal management strategies for lithium-ion battery systems.
Abstract (es)
Contexto: El rendimiento de refrigeración de una batería térmica desempeña un papel fundamental en su eficiencia, vida útil y seguridad. Esta importancia se debe al calor generado durante los procesos de carga y descarga. A medida que aumentan las temperaturas, las características clave de la batería se ven significativamente afectadas
Método: Utilizando el software de dinámica de fluidos computacional ANSYS Fluent, se realizó una simulación numérica 2D para estudiar el enfriamiento de una batería de iones de litio en presencia de nanofluidos. El flujo de nanofluidos se analizó utilizando el modelo de mezcla multifásica.
Resultados: Se observó que la velocidad de entrada del refrigerante afecta significativamente la distribución de temperatura del módulo y la diferencia máxima de temperatura, donde las diferencias de temperatura prácticamente se estabilizan para velocidades de entrada superiores a 0.3 m/s. Se estudió el efecto del uso de nanofluidos con tres tipos diferentes de nanopartículas (alúmina, cobre y fullereno) dispersas en agua como fluido base. Los resultados muestran que la diferencia de temperatura en el módulo varía según la naturaleza y la fracción de volumen de las nanopartículas. La incorporación de nanofluidos produce una reducción significativa en la temperatura del módulo. Se observó que las nanopartículas de fullereno presentan un rendimiento de refrigeración superior al de otros tipos de nanopartículas. Por otro lado, una fracción de volumen de nanopartículas superior al 2 % da como resultado una distribución de temperatura prácticamente uniforme dentro del módulo, así como una reducción en la temperatura de la celda.
Conclusiones: Los nanofluidos tienen un efecto importante en la refrigeración de las baterías. Optimizar la concentración de nanopartículas y la dinámica del flujo puede mejorar eficazmente las estrategias de gestión térmica de los sistemas de baterías de iones de litio.
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