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    Validation case: Conjugate Heat Transfer in a Battery Pack

    The aim of this project is to demonstrate the validity of SimScale’s CHTv2 solver by performing a conjugate heat transfer analysis of a battery pack by comparing the following parameter:

    •  Local temperatures at available thermocouple locations

    The simulation results of SimScale were compared to the results presented in [1]. Code Verification is also carried out by comparing the CHT v2 results to Fluent results.


    The validation case consists of two geometries Battery_Pack and Battery_Pack_v2. Both are essentially same however Battery_Pack_v2 is devoid of redundant face splits as compared to Battery_Pack.


    The geometry can be seen below:

    battery pack cad model
    Figure 1: The CAD model of the battery pack that was used for the conjugate heat transfer analysis

    It represents a 1:1 model reverse-engineered from images in the publication. The battery pack consists of 32 (8×4) cell configuration.
    The thermocouple location on the leeward side of the cells has been used for validating the CHT v2 solver:

    thermocouple locations on battery pack
    Figure 2: The placement of the thermocouple locations on the battery pack

    The thermocouple readings from cells 3, 19 and 31 have been used for the comparison:

    cells whose thermocouple reading was used for comparison
    Figure 3: For the comparison the thermocouple reading from cell 3 in row 1, cell 19 in row 3 and cell 31 in row 4 were used.

    Analysis Type and Mesh

    Tool Type: OpenFOAMⓇ

    Analysis Type: Compressible, steady-state analysis with the Conjugate Heat Transfer v2 (CHT v2) solver.

    Mesh and Element Types:

    The Standard mesher algorithm with tetrahedral and hexahedral cells was used to generate the mesh. A mesh sensitivity analysis has been carried out to determine the dependence of the CHTv2 solver temperature predictions on the mesh, while using lead as the material of the cells:

    Mesh TypeNumber of cells/nodesTemperature@L1-cell3 [\(°C\)]Temperature@L1-cell19 \([°C]\)Temperature@L1-cell31 \([°C]\)
    Mesh 13.6M cells, 1.1M nodes29.53531.06526.816
    Mesh 211.2M cells, 3.5M nodes30.79431.11427.218
    %TC deviation (Mesh 2 – Mesh 1)4.0890.1571.477
    Table 1: The results of the mesh sensitivity analysis indicate the deviation of the temperature on specific points of interest between the two different configurations.

    Maximum temperature deviation of 1.2 \(°C\) (~4.1%) between Mesh 1 and Mesh 2, was observed at leeward side of cell 3. In the following figure the percentage of temperature deviation in degrees Celsius (% TC) at measurement location L1 is displayed for three different mesh configurations as well:

    temperature deviation between mesh 1 and mesh 2 cht battery pack
    Figure 4: It is revealed from the mesh sensitivity study that the biggest deviation in temperature between the two meshes was observed in cell 3, and the smallest one in cell 19.

    In order to estimate the physical properties of the cells, a material sensitivity study has also been carried out, using three different materials:

    • Lead (low conductivity)
    • Aluminium (medium conductivity)
    • Copper (high conductivity)

    Comparing L1 temperatures for the three materials, according to the diagrams below, aluminium cells show the closest match:

    • to thermocouple readings at all three measurement cells (3,19 and 31);
    • to ANSYS Fluent predictions at all three measurement cells (3,19 and 31). 
    material study and temperature deviation at different cells
    Figures 5: Aluminum was proved to be the material with the smallest temperature deviation for all three cells compared to the experimental data, and the results from the Fluent software.

    Hence, based on the material and mesh sensitivity analyses, aluminum cells and “Mesh 2” have been used for the final validation.

    mesh details and zoom in to the cells inside the battery
    Figure 6: “Mesh 2” used for the case after the sensitivity study is a fine mesh with tetrahedral and hexahedral cells.

    Simulation Setup

    Fluid Material:

    • Air
      • Dynamic viscosity \((\mu)\) = 1.83e-5 \(m^2 \over\ s\)
      • Specific heat = 1004 \(J \over\ (kg \times\ K)\)

    Solid Materials:

    • Wood
      • Isotropic
      • Thermal conductivity \((k)\) = 0.16 \(W \over\ (m \times\ K)\)
      • Specific heat = 1260 \(J \over\ (kg \times\ K)\)
      • Density \((\rho)\) = 500 \(kg \over\ m^3\)
    • Aluminum
      • Isotropic
      • Thermal conductivity \((k)\) = 235 \(W \over\ (m \times\ K)\)
      • Specific heat = 897 \(J \over\ (kg \times\ K)\)
      • Density \((\rho)\) = 2700 \(kg \over\ m^3\)

    Boundary Conditions:

    • Room temperature, \((T)\) = 23 \(°C\)
    • Inlet velocity = 3.45 \(m \over\ s\)
    • Outlet pressure = 101325 \(Pa\) (fixed value)
    • Absolute power = 2.75 \(W\) per cell 
    • No-slip walls
    boundary conditions applied on battery pack
    Figure 7: A schematic representation of the boundary conditions applied on the model

    Result Comparison

    Convergence below 1e-3 has been achieved. Calculated physical quantities such as inlet pressure, outlet velocity, and cell average temperatures have also been allowed to converge to stable values:

    residuals and results cht battery pack simscale
    Figures 8: The graphs for the Residuals, inlet’s pressure, outlet’s velocity and average temperature of the faces of a random cell above are a good indication that the simulation is converged and reliable.

    The final temperature values are displayed in the following table:

    Cell No.TC@m2-SimScale-Aluminium \([°C]\)Experiment \([°C]\)CFD_fluent \([°C]\)
    Table 2: The temperature on cells 3, 19 and 33 extracted from the SimScale, experimental and Fluent studies.

    Comparing CHTv2 solver predictions to thermocouple readings@L1, temperature deviations of:

    • Cell 3: 0.9 \(°C\) (3%)
    • Cell 19: 0.5 \(°C\) (1.8%)
    • Cell 31:  3.77 \(°C\) (12%)

    The temperature deviations predicted from the CHTv2 solver are in good comparison with ANSYS Fluent. SimScale under predicts the temperature for all cells tested, however it is still close to the other results.

    results comparison graph between SimScale and experimental data and fluent
    Figure 9: It is apparent that SimScale slightly under predicts the temperature compared to the other two result sets for all three cells.

    To have a more analytical look at the deviation between the experimental data and the results for the two software, you can also check the following graph:

    deviation graph between SimScale and experimental data
    Figure 10: A closer look at the deviation of the two CFD tools’ results with the experimental data

    The source of these deviations could be that:

    1. The orientation of the battery arrangement within the battery pack has been misrepresented in the publication (experimental setup);
    2. The battery material has been approximated via a sensitivity study.

    In the following image, the temperature distribution across the flow domain indicates the heat transfer from cells to the air inside the battery pack. The cutting plane displayed is normal to the z axis:

    temperature distribution on cutting plane across battery pack  created in the post-processor
    Figure 11: The temperature distribution on a plane normal to the z-axis displays the heat transfer between the components of the battery pack (especially the cells) and the flow domain


    If you still encounter problems validating you simulation, then please post the issue on our forum or contact us.

    Last updated: October 11th, 2022