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Nanofluid-based cooling of prismatic lithium-ion battery packs: an integrated numerical and statistical approach

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Abstract

Recently, the need for thermal management of lithium-ion batteries in electrical transportation engineering has received increased attention. To get maximum performance from lithium-ion batteries, battery thermal management systems are required. This paper quantitatively presents the effects of several factors on both maximum battery temperature and temperature gradient. These factors include ambient temperature (288 K, 293 K, 298 K, 303 K, 308 K), C-rate (1C, 2C, 3C, 4C, 5C), mixing ratio (1%, 2%, 3%, 4%, 5%), and inlet velocity (0.01 m s−1, 0.02 m s−1, 0.03 m s−1, 0.04 m s−1, 0.05 m s−1). Five levels for each parameter were considered to develop the orthogonal array. The significance of the variables was orderly shown through the L25 experiment. Results indicated that for maximal battery temperature, C-rate and ambient temperature are the most significant factors while for temperature gradient, C-rate and inlet velocity play an important role. For maximum battery temperature ambient temperature, C-rate, mixing ratio, and inlet velocity of 288 K, 1C, 4%, and 0.05 m s−1, respectively, were obtained at the optimal setting. An ambient temperature of 308 K, a C-rate of 1, a mixing ratio of 5%, and an inlet velocity of 0.05 m s−1 was the optimal setting for the temperature gradient. The results showed that the confirmatory test validates the optimization process for maximum battery temperature and temperature gradient. This study may provide a pathway for manufacturers and researchers interested in minimizing battery temperature and improving temperature gradient in electric vehicle applications.

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Abbreviations

\(C_{{\text{p}}}\) :

Specific heat (J kg−1 K−1)

dp:

Diameter (nm)

DoD:

Depth of discharge

H2O:

Water

j ECh :

Volumetrically current transfer ratio

j short :

Current transfer ratio

k :

Thermic conductivity (W mK−1)

K bz :

The Boltzmann constant (J K−1)

n :

Size of electrons

ρ :

Density (kg m−3)

Pr:

Prandtl number

Re:

Reynolds number

SOC:

State of charge

SOE:

State of energy

t :

Time (s)

T :

Temperature (K)

T max :

Max of temperature (K)

u :

Velocity (m s−1)

\(V\) :

Operational voltage (V)

V inlet :

The air inlet speed (m s−1)

bf:

Base fluid

nf:

Nanofluid

p:

Nanoparticle

+:

Positive electrodes

−:

Negative electrodes

µ :

Viscosity (kg ms−1)

σ :

Effective electric conductivities

\(\emptyset\) :

The volume fraction of nanoparticles

φ :

Phase potentials

NTGK:

Newman, Tiedemann, Gu and Kim

PCM:

Phase change materials

3D:

Three-dimensional

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Author information

Authors and Affiliations

  1. Department of Chemical Engineering, Eskisehir Osmangazi University, 26040, Eskisehir, Turkey

    Ugur Morali

  2. Department of Mechanical Engineering, Eskisehir Osmangazi University, 26040, Eskisehir, Turkey

    Ozge Yetik

  3. Faculty of Aeronautics and Astronautics, Eskisehir Technical University, 26000, Eskisehir, Turkey

    Tahir Hikmet Karakoc

  4. Information Technology Research and Application Center, Istanbul Ticaret University, Istanbul, Turkey

    Tahir Hikmet Karakoc

Authors
  1. Ugur Morali
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  2. Ozge Yetik
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  3. Tahir Hikmet Karakoc
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Contributions

OY, UM contributed to conceptualization, methodology, software, data curation, writing—original draft, visualization, investigation, validation, supervision, writing—review and editing. THK contributed to validation, supervision, writing—review and editing.

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Correspondence to Ugur Morali.

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Morali, U., Yetik, O. & Karakoc, T.H. Nanofluid-based cooling of prismatic lithium-ion battery packs: an integrated numerical and statistical approach. J Therm Anal Calorim 149, 799–811 (2024). https://doi.org/10.1007/s10973-023-12726-9

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  • DOI: https://doi.org/10.1007/s10973-023-12726-9

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