<p>Effective thermal regulation of lithium-ion battery modules is a critical requirement for safe and durable electric vehicle (EV) operation. This study presents a comprehensive multi-parametric computational fluid dynamics (CFD) investigation of a liquid-based battery thermal management system (BTMS), validated against controlled laboratory experiments. Six coolant fluids such as water, ethylene glycol, water–glycol mixture (50:50), propylene glycol, ethyl alcohol, and glycerol were systematically evaluated across five inlet velocities (1–5&#xa0;m&#xa0;s<sup>−1</sup>) and three discharge rates (1C, 2C, 3C) within a lightweight aluminum serpentine cooling channel coupled with a zigzag-configured 18,650 Li-ion battery module, yielding 90 unique simulation scenarios. Performance was assessed based on maximum battery surface temperature, module-level temperature gradient (ΔT), convective heat transfer coefficient, friction factor, and coefficient of performance (COP). Water demonstrated the best overall thermal–hydraulic balance, achieving the highest convective heat transfer coefficient of 8149.2 W&#xa0;m<sup>−2&#xa0;</sup>K<sup>−1</sup> at 2C and 2&#xa0;m&#xa0;s<sup>−1</sup>, with a superior COP of 247.0. Ethylene Glycol produced the narrowest temperature gradient (ΔT = 22.96&#xa0;°C) under 3C discharge, indicating superior spatial thermal uniformity, though at a lower COP of 93.0 due to its high viscosity. Statistical analysis across all 90 scenarios confirmed that increasing coolant velocity beyond 3&#xa0;m&#xa0;s<sup>−1</sup> yielded negligible thermal improvement (less than 1&#xa0;°C) while substantially increasing hydraulic penalties. The CFD model was validated against experiments with an average absolute error below 2.5%. The findings provide actionable guidelines for coolant selection and flow velocity optimization in compact, lightweight BTMS architectures for next-generation EVs.</p>

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CFD investigations on appropriate liquid for battery thermal management systems in electric vehicles based on effective heat transfer rate

  • Nandana Mahesh,
  • Laxana Sourirajan,
  • Mohankumar Subramanian,
  • Beena Stanislaus Arputharaj,
  • Arunkumar Karuppasamy,
  • Pradesh Sakthivel,
  • Parvathy Rajendran,
  • Subhav Singh,
  • Vijayanandh Raja

摘要

Effective thermal regulation of lithium-ion battery modules is a critical requirement for safe and durable electric vehicle (EV) operation. This study presents a comprehensive multi-parametric computational fluid dynamics (CFD) investigation of a liquid-based battery thermal management system (BTMS), validated against controlled laboratory experiments. Six coolant fluids such as water, ethylene glycol, water–glycol mixture (50:50), propylene glycol, ethyl alcohol, and glycerol were systematically evaluated across five inlet velocities (1–5 m s−1) and three discharge rates (1C, 2C, 3C) within a lightweight aluminum serpentine cooling channel coupled with a zigzag-configured 18,650 Li-ion battery module, yielding 90 unique simulation scenarios. Performance was assessed based on maximum battery surface temperature, module-level temperature gradient (ΔT), convective heat transfer coefficient, friction factor, and coefficient of performance (COP). Water demonstrated the best overall thermal–hydraulic balance, achieving the highest convective heat transfer coefficient of 8149.2 W m−2 K−1 at 2C and 2 m s−1, with a superior COP of 247.0. Ethylene Glycol produced the narrowest temperature gradient (ΔT = 22.96 °C) under 3C discharge, indicating superior spatial thermal uniformity, though at a lower COP of 93.0 due to its high viscosity. Statistical analysis across all 90 scenarios confirmed that increasing coolant velocity beyond 3 m s−1 yielded negligible thermal improvement (less than 1 °C) while substantially increasing hydraulic penalties. The CFD model was validated against experiments with an average absolute error below 2.5%. The findings provide actionable guidelines for coolant selection and flow velocity optimization in compact, lightweight BTMS architectures for next-generation EVs.