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Numerical analysis of LiFePo4 battery thermal management system using cold plate

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Abstract

Lithium-ion batteries are widely used in electric vehicles because of their high capacity and voltage. However, some drawbacks to the battery stability exist. The aim of our research was to determine the optimum width and number of channels of a cold plate. To estimate the temperature distribution and heat transfer rate, the MSMD (multi-scale multi-dimensional) - Newman P2D model in ANSYS Fluent was used. Prior to comparing the heat transfer rates of the various battery surfaces using different cold plates, the surface temperature of the battery (LiFePO4) at discharge rates of 2C, 3C, and 4C was calculated to determine the battery characteristics. Subsequently, two cold plates were attached to both sides (front and back) of the batteries and the heat transfer rate of the battery surface in contact with the cold plate, and the pressure drop between the inlet and outlet of the channels during the discharge process were estimated. In addition, the j and f factors, which are used to estimate the cooling performance of the cold plates, were calculated. In determining the most efficient cold plate options, the trade-off between the heat transfer coefficient and the pressure drop is also important for the relationship between the two factors (j and f factors).

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Abbreviations

ΔP :

Pressure drop across plate [Pa]

A :

Surface area [m2]

c p :

Specific heat at constant pressure [J/(kg·°C)]

D h :

Hydraulic diameter [m]

f :

Friction factor

h :

Heat transfer coefficient [W/(m2·°C)]

j :

Colburn factor

K :

Thermal conductivity [W/(m·°C)]

L :

Characteristic length [m]

Nu :

Nusselt number

P :

Static pressure [Pa]

Pr :

Prandtl number

Re :

Reynolds number

T :

Static temperature [K]

ṁ :

Mass flow rate [kg/s]

\(\dot{Q}\) :

Heat generation rate [W]

b :

Battery

max :

Maximum

avg :

Average

s :

Surface

c :

Channel

in :

Inlet

out :

Outlet

w :

Water

μ :

Dynamic viscosity [Pas]

σ :

Standard deviation [°C]

ρ :

Density [kg/m3]

ICE :

Internal combustion engine

EV :

Electric vehicle

IR :

Infrared

PCU :

Power control unit

BTMS :

Battery thermal management system

CFD :

Computational fluid dynamics

MSMD :

Multi-scale multi-dimensional

P2D :

Pseudo-2D

LiFePO4 :

Lithium iron phosphate

LHS :

Latin hypercube sampling

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Acknowledgments

This research was financially supported by the Ministry of Trade, Industry, and Energy (MOTIE), Korea, under the “Regional Specialized Industry Development Program” (S3193 127) supervised by the Korea Institute for Advancement of Technology (KIAT), and supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry, and Energy (MOTIE) (No. 202230 30030110).

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Authors and Affiliations

  1. Department of Precision Mechanical Engineering, Kyungpook National University, Sangju, 37224, Korea

    Seyeon Hwang, Rakjun Choi & Seolha Kim

  2. Department of Mechanical Engineering, Gyeongsang National University, Jinju, 52828, Korea

    Seyeon Hwang

  3. Department of Advanced Science and Technology Convergence, Kyungpook National University, Sangju, 37224, Korea

    Seolha Kim

  4. Hanyung Alcobis Co. Ltd., Naju, 58209, Korea

    Minjae Song

  5. Neutron Science Division, Korea Atomic Energy Research Institute, Deajeon, 34057, Korea

    TaeJoo Kim

Authors
  1. Seyeon Hwang
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  2. Rakjun Choi
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  3. Seolha Kim
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  4. Minjae Song
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  5. TaeJoo Kim
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Corresponding author

Correspondence to Seolha Kim.

Additional information

Hwang Seyeon received her Bachelor’s at Kyungpook National University (South Korea), in the Department of Precision Mechanical Engineering, and now works at Gyeongsang National University for her Master’s.

Kim SeolHa graduated from POSTECH, Bachelor’s (Mechanical Engineering), and Doctorate (Nuclear Engineering). He worked at the Korea Atomic Energy Research Institute and the Chinese Academy of Science as a researcher. Currently, he is working in Kyungpook National University as a Professor.

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Hwang, S., Choi, R., Kim, S. et al. Numerical analysis of LiFePo4 battery thermal management system using cold plate. J Mech Sci Technol 37, 3163–3171 (2023). https://doi.org/10.1007/s12206-023-0540-4

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  • DOI: https://doi.org/10.1007/s12206-023-0540-4

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