In my research, I focus on the thermal management of an EV battery pack operating under extreme environmental conditions. The growing demand for high-performance electric vehicles requires battery systems to maintain safe temperature windows during high-rate discharges and to recover quickly after cold soaking. I proposed and investigated a novel architecture that couples microchannel liquid cooling with phase change material (PCM) in a honeycomb-inspired layout. This design enables simultaneous heat dissipation, low-temperature preheating, and passive thermal insulation within a single integrated structure. In the following sections, I describe the modelling approach, the numerical validation, the parametric studies for cooling performance, and the preheating/insulation analysis.
Motivation and Design Concept
The EV battery pack is the core energy storage unit of electric vehicles. Lithium-ion cells offer high energy density and long cycle life, but their performance is strongly temperature dependent. High temperatures accelerate degradation and may lead to thermal runaway; low temperatures increase internal resistance and reduce available capacity. In addition, large battery modules often suffer from poor temperature uniformity, which further shortens life. Therefore, an efficient thermal management system must satisfy three objectives: keep the maximum temperature below a critical limit, maintain the temperature difference across cells below 5°C, and enable rapid heating in cold environments.
Conventional single-mode cooling systems, such as air cooling or liquid cooling alone, cannot simultaneously address these requirements. Passive PCM cooling offers excellent temperature uniformity but has limited heat absorption capacity under sustained high-rate discharge. Active liquid cooling provides high heat removal but may create larger temperature gradients. I therefore combined both approaches in a honeycomb-like module, where each cylindrical cell is surrounded by a composite PCM matrix and embedded within an aluminium frame containing vertical microchannels. Water flowing through the microchannels exchanges heat directly with the frame, while the PCM buffers transient heat peaks and homogenizes the temperature field. During cold conditions, the same microchannels can deliver warm fluid to preheat the EV battery pack, and the PCM acts as a thermal reservoir to extend the cooling-down period.
Electrochemical-Thermal Modelling of the Cell
I selected a commercial 18650 cylindrical lithium iron phosphate (LiFePO4) cell with a nominal capacity of 1.5 Ah. The cell geometry is simplified as a homogeneous solid cylinder with diameter 18 mm and height 65 mm. The averaged thermophysical properties are summarized in Table 1.
| Parameter | Value |
|---|---|
| Density, \(\rho\) | 2180 kg/m³ |
| Specific heat capacity, \(c_p\) | 1066 J/(kg·K) |
| Radial thermal conductivity, \(k_r\) | 1.1 W/(m·K) |
| Circumferential thermal conductivity, \(k_\phi\) | 1.1 W/(m·K) |
| Axial thermal conductivity, \(k_z\) | 12.5 W/(m·K) |
The heat generation inside the cell was described using the simplified Bernardi model. The total heat generation rate per unit volume \(q\) is expressed as
$$ q = \frac{I}{V_0} \left[ \left( E_{OC} – E \right) – T \frac{\partial E_{OC}}{\partial T} \right] + \frac{I^2 \left( R_\Omega + R_P \right)}{V_0}, $$
where \(I\) is the current, \(V_0\) is the cell volume, \(E_{OC}\) is the open-circuit voltage, \(E\) is the operating voltage, \(T\) is the temperature, and \(R_\Omega + R_P\) is the sum of ohmic and polarization resistances. For this cell, the internal resistance as a function of temperature is given by
$$ R_\Omega + R_P = -0.0001 T^3 + 0.0134 T^2 – 0.5345 T + 12.407. $$
Using the above equations, I computed the volumetric heat generation rates at 35°C. The results are listed in Table 2.
| Discharge rate | Current (A) | Heat generation rate (W/m³) |
|---|---|---|
| 1C | 1.5 | 5,362 |
| 2C | 3.0 | 30,586 |
| 3C | 4.5 | 60,156 |
| 4C | 6.0 | 126,758 |
To verify the heat generation model, I compared the simulated temperature rise of a single cell with available experimental data. The cell was wrapped in a thermal insulation foam and discharged at 3C for 1200 s in a 20°C environment. The maximum temperature difference between simulation and experiment was only 0.64°C, confirming that the model is suitable for subsequent system-level simulations.
Numerical Model of the Coupled BTMS
I designed the EV battery pack thermal management system using a 4×4 staggered arrangement of 18650 cells. The overall structure is shown schematically below. The image illustrates the concept of a battery pack with integrated thermal management:
The aluminium frame has a thickness of 1.5 mm and a height of 65 mm. Each cell is separated from the frame by a 1.25 mm gap filled with composite PCM. Circular microchannels with a diameter of 1 mm were placed inside the aluminium frame. The baseline design (Case 1) contains 63 channels, with one channel located at the centre of each of the six sides of the honeycomb cell. Case 2 contains 111 channels, adding channels at the corners, and Case 3 contains 174 channels, adding channels at the one-third points as well. Figure numbers are omitted here, but the three channel layouts were compared under identical total flow rate.
The governing equations for the cooling water in microchannels are:
$$ \frac{\partial \rho_w}{\partial t} + \nabla \cdot (\rho_w \mathbf{v}) = 0, $$
$$ \frac{\partial (\rho_w \mathbf{v})}{\partial t} + \nabla \cdot (\rho_w \mathbf{v} \mathbf{v}) = -\nabla p + \nabla \cdot (\mu_w \nabla \mathbf{v}), $$
$$ \frac{\partial (\rho_w c_{p,w} T_w)}{\partial t} + \nabla \cdot (\rho_w c_{p,w} \mathbf{v} T_w) = \nabla \cdot (\lambda_w \nabla T_w), $$
where \(\rho_w\), \(c_{p,w}\), \(\lambda_w\), and \(\mu_w\) are the density, specific heat, thermal conductivity, and dynamic viscosity of water, respectively.
For the PCM, I used the enthalpy-porosity method. The energy equation is
$$ \rho_{PCM} \frac{\partial H}{\partial t} = \lambda_{PCM} \nabla^2 T, $$
where \(H = h_{sen} + \Delta H\). The sensible enthalpy is
$$ h_{sen} = \int_{T_0}^{T} c_{p,PCM} \, dT, $$
and the latent enthalpy is \(\Delta H = \beta L\), where \(L\) is the latent heat of fusion and \(\beta\) is the liquid fraction, defined as
$$ \beta = \begin{cases} 0 & T < T_s \\ \dfrac{T – T_s}{T_l – T_s} & T_s \le T \le T_l \\ 1 & T > T_l \end{cases}. $$
The composite PCM consisted of paraffin and expanded graphite. Table 3 lists the thermophysical properties for different graphite mass fractions.
| Graphite mass fraction (%) | Thermal conductivity (W/m·K) | Density (kg/m³) | Specific heat (J/kg·K) | Latent heat (J/g) | Phase change temperature (°C) |
|---|---|---|---|---|---|
| 0 | 0.245 | 800 | 2300 | 200.66 | 37 |
| 2 | 0.324 | 800 | 2260 | 196.65 | 37 |
| 5 | 0.907 | 800 | 2200 | 191.37 | 37 |
| 8 | 1.374 | 800 | 2140 | 184.61 | 37 |
| 10 | 1.687 | 800 | 2100 | 180.60 | 37 |
| 15 | 2.499 | 800 | 2000 | 170.56 | 37 |
| 20 | 3.355 | 800 | 1900 | 160.53 | 37 |
I performed transient CFD simulations using ANSYS Fluent. The following settings were applied:
- Pressure-based solver, transient mode
- Energy equation activated; laminar flow model for water (Re < 2300)
- Solidification/melting model for PCM
- Water inlet: velocity inlet at specified temperature
- Outlet: pressure outlet with backflow temperature
- Convective boundary condition on external surfaces: 10 W/(m²·K) for the aluminium frame and 5 W/(m²·K) for the PCM surface
- SIMPLE scheme for pressure-velocity coupling; second-order upwind spatial discretization
- Convergence criteria: residual < 10⁻⁶
- Time step: 2 s, maximum 20 iterations per step
A grid independence study was conducted with four mesh densities: 1,166,891; 1,971,858; 3,802,869; and 7,464,891 cells. The maximum temperature changed only slightly when the mesh count increased beyond 1,971,858. Therefore, I selected the mesh with 1,971,858 cells for all subsequent simulations.
Cooling Performance Evaluation
Comparison of PCM cooling and PCM-microchannel cooling
First, I compared two cooling strategies for the EV battery pack: passive PCM cooling only and the proposed PCM coupled with microchannel liquid cooling (PCM-MCHS). The ambient temperature was 35°C, the discharge rate was 4C, and the water inlet velocity was 0.1 m/s. The results at the end of the 900 s discharge are summarized in Table 4.
| System | Maximum temperature (°C) | Maximum temperature difference (°C) | Final liquid fraction |
|---|---|---|---|
| PCM only | 41.98 | 3.50 | 0.90 |
| PCM-MCHS | 39.83 | 2.95 | 0.33 |
The PCM-MCHS system reduced the maximum temperature by 2.15°C and the maximum temperature difference by 0.55°C compared to the PCM-only design. The liquid fraction of the PCM decreased significantly because the microchannels removed heat continuously, preventing the PCM from fully melting. This confirms that the active liquid cooling effectively extends the heat absorption capacity of the PCM.
Effect of the number of microchannels
I varied the channel layout while maintaining a constant total flow rate. The total flow rate of Case 1 at 0.1 m/s was taken as the reference. The corresponding inlet velocities for Case 2 and Case 3 were 0.0567 m/s and 0.0362 m/s, respectively. Table 5 presents the simulated results at the end of discharge.
| Case | Number of channels | Inlet velocity (m/s) | Tmax (°C) | ΔT (°C) | Liquid fraction |
|---|---|---|---|---|---|
| Case 1 | 63 | 0.1000 | 39.83 | 2.94 | 0.33 |
| Case 2 | 111 | 0.0567 | 39.82 | 3.14 | 0.24 |
| Case 3 | 174 | 0.0362 | 40.09 | 3.51 | 0.25 |
Increasing the channel number while keeping the total flow rate constant increased the heat transfer area but also reduced the flow velocity in each channel. Case 2 showed no significant improvement in the maximum temperature, and Case 3 worsened both temperature and uniformity. Therefore, Case 1 was selected as the optimal baseline for cooling.
Effect of coolant velocity
Using Case 1, I simulated inlet velocities of 0.05, 0.1, and 0.2 m/s. The maximum temperature and temperature difference at the end of 4C discharge are shown in Table 6.
| Velocity (m/s) | Tmax (°C) | ΔT (°C) | Final liquid fraction |
|---|---|---|---|
| 0.05 | 40.25 | 3.02 | 0.38 |
| 0.10 | 39.83 | 2.94 | 0.33 |
| 0.20 | 39.63 | 2.91 | 0.29 |
The maximum temperature decreased gradually with increasing velocity, but the difference between 0.1 and 0.2 m/s was only 0.20°C. Therefore, 0.1 m/s provides a good balance between cooling performance and pumping power.
Effect of graphite mass fraction in PCM
I evaluated seven graphite mass fractions (0, 2, 5, 8, 10, 15, 20%) under the baseline cooling conditions (Case 1, 0.1 m/s, 4C, ambient 35°C). Table 7 lists the key results.
| Graphite (%) | Tmax (°C) | ΔT (°C) | Final liquid fraction |
|---|---|---|---|
| 0 | 40.80 | 3.05 | 0.60 |
| 2 | 40.06 | 3.10 | 0.37 |
| 5 | 39.83 | 2.94 | 0.33 |
| 8 | 39.42 | 3.16 | 0.28 |
| 10 | 39.25 | 3.22 | 0.25 |
| 15 | 38.91 | 3.31 | 0.22 |
| 20 | 38.66 | 3.28 | 0.21 |
Higher graphite content increases the thermal conductivity of the PCM, which improves heat removal from the cells. However, the improvement becomes marginal beyond 5%. Moreover, excessive graphite raises the electrical conductivity of the PCM, increasing the risk of short circuits. Therefore, I chose 5% graphite as the optimal mass fraction for the EV battery pack thermal management system.
Effect of coolant flow direction
I compared co-current flow (all channels from top to bottom) with counter-current flow (adjacent channels in opposite directions) using the Case 2 channel layout. The inlet velocity was 0.1 m/s, graphite content was 5%, and discharge was 4C. The results are shown in Table 8.
| Configuration | Tmax (°C) | ΔT (°C) | Final liquid fraction |
|---|---|---|---|
| Co-current | 39.83 | 3.15 | 0.25 |
| Counter-current | 39.80 | 2.77 | 0.29 |
The counter-current arrangement improved temperature uniformity by 0.38°C and increased the PCM liquid fraction, indicating better utilization of the latent heat capacity. The temperature distribution across the battery module became more symmetric, which is beneficial for cell balancing.
Low-Temperature Preheating and Insulation Performance
Thermal insulation capability
To evaluate the insulation effect of the PCM, I initialized the EV battery pack at 50°C and placed it in a -10°C environment for 10 hours without any active heating. I compared cases with different graphite mass fractions and a control without PCM. The time required for the battery temperature to drop below 0°C is summarized in Table 9.
| Configuration | Time to reach 0°C (h) |
|---|---|
| No PCM | ~1.0 |
| 0% graphite | > 8.0 |
| 5% graphite | ~5.5 |
| 8% graphite | ~4.8 |
| 10% graphite | ~4.2 |
| 15% graphite | ~3.5 |
| 20% graphite | ~3.0 |
Pure paraffin provided the best insulation because of its low thermal conductivity and high latent heat. However, for active preheating, a higher thermal conductivity is desirable. A balance must be struck between insulation and heating rate.
Preheating performance evaluation parameters
In the preheating study, I set the initial temperature of the EV battery pack to -20°C, the ambient temperature to -20°C, and the inlet fluid temperature to 25°C. The goal was to bring the coldest spot on the battery surface to 20°C. I defined the temperature rise rate \(RTR\) as
$$ RTR = \frac{20 – (-20)}{\tau}, $$
where \(\tau\) is the time required to reach 20°C. I also monitored the maximum temperature difference \(\Delta T\) at the end of preheating.
Effect of graphite mass fraction on preheating
Using Case 1 with an inlet velocity of 0.1 m/s and top-to-bottom flow, I simulated seven graphite fractions. The results are listed in Table 10.
| Graphite (%) | Preheating time (s) | RTR (°C/min) | ΔT (°C) |
|---|---|---|---|
| 0 | 405 | 5.93 | 1.90 |
| 2 | 360 | 6.67 | 2.35 |
| 5 | 272 | 8.82 | 2.80 |
| 8 | 256 | 9.38 | 3.05 |
| 10 | 250 | 9.60 | 3.12 |
| 15 | 240 | 10.00 | 3.20 |
| 20 | 235 | 10.21 | 3.25 |
The preheating time dramatically decreased from 405 s to 272 s when the graphite fraction increased from 0% to 5%. Beyond 5%, the additional reduction was only 37 s even when increasing to 20%. Meanwhile, the temperature difference increased slightly. Therefore, 5% graphite remains the optimal choice for both cooling and preheating.
Effect of fluid velocity on preheating
Using the 5% graphite PCM and Case 1 channel layout, I varied the inlet velocity. Table 11 presents the preheating results.
| Velocity (m/s) | Preheating time (s) | RTR (°C/min) | ΔT (°C) |
|---|---|---|---|
| 0.05 | 380 | 6.32 | 2.20 |
| 0.10 | 272 | 8.82 | 2.80 |
| 0.25 | 211 | 11.37 | 3.32 |
| 0.50 | 186 | 12.90 | 3.50 |
| 1.00 | 169 | 14.20 | 3.60 |
As expected, higher velocity shortens the preheating time. The marginal benefit diminishes beyond 0.25 m/s. The temperature difference also increases with velocity. Thus, I selected 0.25 m/s as the optimum preheating flow velocity, balancing heating speed, temperature uniformity, and pump power.
Effect of channel number on preheating
To maintain the same total flow rate, I set the inlet velocities for Case 1, Case 2, and Case 3 as 0.25, 0.1418, and 0.0905 m/s, respectively. The results are shown in Table 12.
| Case | Number of channels | Inlet velocity (m/s) | Preheating time (s) | RTR (°C/min) | ΔT (°C) |
|---|---|---|---|---|---|
| Case 1 | 63 | 0.2500 | 211 | 11.37 | 3.32 |
| Case 2 | 111 | 0.1418 | 192 | 12.50 | 3.65 |
| Case 3 | 174 | 0.0905 | 181 | 13.26 | 4.50 |
More channels reduce the preheating time because the heat transfer area increases. However, the temperature difference becomes larger due to the more pronounced entrance effect. Case 2 offers a reasonable compromise, reducing the heating time by 19 s compared to Case 1 while keeping the temperature difference within 4°C. I therefore adopted Case 2 for the subsequent flow-direction study.
Effect of flow direction on preheating
Using the Case 2 geometry with an inlet velocity of 0.1418 m/s and 5% graphite PCM, I compared co-current and counter-current arrangements. The results are listed in Table 13.
| Configuration | Preheating time (s) | RTR (°C/min) | ΔT (°C) |
|---|---|---|---|
| Co-current | 192 | 12.50 | 3.65 |
| Counter-current | 194 | 12.37 | 3.25 |
The counter-current flow slightly increased the heating time by 2 s but significantly improved temperature uniformity by 0.4°C. The more uniform temperature distribution inside the EV battery pack is beneficial to reduce the risk of localized over-heating and uneven degradation. Hence, the counter-current layout is preferred for the preheating mode.
Effect of preheating fluid temperature
I simulated combinations of ambient temperatures (-40, -30, -20, -10°C) and preheating fluid temperatures (25, 35, 40, 45°C) using the Case 2 layout. Table 14 shows the time required for the minimum battery temperature to reach 20°C.
| Ambient (°C) | Fluid 25°C | Fluid 35°C | Fluid 40°C | Fluid 45°C |
|---|---|---|---|---|
| -40 | 223 | 146 | 122 | 119 |
| -30 | 208 | 138 | 115 | 112 |
| -20 | 192 | 130 | 109 | 106 |
| -10 | 177 | 121 | 103 | 100 |
Increasing the preheating fluid temperature is more effective than raising the ambient temperature. For example, at -40°C, increasing the fluid temperature from 25°C to 35°C reduces the heating time by 77 s, while raising the ambient temperature from -40°C to -30°C at a fixed fluid temperature of 25°C reduces the time by only 15 s. However, the corresponding temperature difference increases substantially, as shown in Table 15.
| Ambient (°C) | Fluid 25°C | Fluid 35°C | Fluid 40°C | Fluid 45°C |
|---|---|---|---|---|
| -40 | 6.5 | 11.2 | 14.3 | 16.0 |
| -30 | 5.8 | 10.5 | 13.6 | 15.4 |
| -20 | 3.6 | 9.8 | 12.8 | 14.7 |
| -10 | 2.9 | 8.9 | 11.9 | 13.8 |
When the fluid temperature exceeds the PCM melting temperature of 37°C, the PCM absorbs heat during melting, which slows down the temperature rise and mitigates the temperature difference. This explains why the difference between 40°C and 45°C fluid is smaller than the difference between 25°C and 35°C. Nevertheless, for the EV battery pack, a moderate preheating fluid temperature of 25°C with counter-current flow offers the best trade-off between heating time and thermal uniformity.
Overall System Optimization and Final Parameters
Based on the systematic parametric study, I identified the optimal design and operating parameters for the proposed microchannel-PCM coupled EV battery pack thermal management system. Table 16 summarizes the recommended values.
| Parameter | Recommended value |
|---|---|
| Graphite mass fraction in PCM | 5% |
| Channel layout | Case 2 (111 channels) |
| Cooling fluid inlet velocity | 0.10 m/s |
| Preheating fluid inlet velocity | 0.25 m/s |
| Flow direction | Counter-current |
| Preheating fluid temperature | 25°C |
The final system achieves the following improvements compared to the baseline PCM-only cooling: maximum temperature reduced by 2.15°C, temperature difference reduced by 0.55°C. In the low-temperature condition of -20°C, the preheating time is 192 s with a temperature difference of 3.25°C when using the counter-current arrangement, which fully meets the requirement of bringing the coldest cell to 20°C in less than 4 minutes while keeping the module temperature difference well below 5°C.
Conclusion
In this work, I designed and numerically evaluated a honeycomb-structured microchannel-PCM coupled thermal management system for an EV battery pack. The main conclusions are as follows:
- The coupled system outperforms pure PCM cooling by reducing the maximum temperature and temperature difference simultaneously. It can maintain the EV battery pack below 40°C during 4C discharge at 35°C ambient.
- The optimal graphite mass fraction in the composite PCM is 5%. Beyond this value, further increases in thermal conductivity only provide marginal benefits while raising safety concerns.
- For cooling, an inlet velocity of 0.1 m/s is sufficient. For preheating, an inlet velocity of 0.25 m/s gives the best balance among heating time, temperature uniformity, and pumping loss.
- Increasing the number of microchannels while keeping the total flow rate constant does not always improve cooling performance; Case 2 is the best choice for preheating, while Case 1 performs equally well for cooling.
- Counter-current flow improves temperature uniformity in both cooling and preheating modes. In the cooling mode, the temperature difference is reduced by 0.38°C; in the preheating mode, it is reduced by 0.4°C with only a 2 s increase in heating time.
- The PCM provides effective thermal insulation for the EV battery pack. Pure paraffin can keep the battery above 0°C for more than 8 hours in a -10°C environment, although the 5% graphite composite is preferred for balanced heating and insulation performance.
- Preheating fluid temperature has a stronger influence than ambient temperature on the heating time. However, high fluid temperatures cause larger temperature differences. The PCM melting process helps mitigate the temperature rise when the fluid temperature exceeds 37°C.
The proposed BTMS offers a compact, integrated solution that satisfies the multi-functional requirements of heat dissipation, preheating, and thermal insulation for an EV battery pack. Future work may include experimental validation under dynamic drive cycles and the development of advanced control strategies to adaptively switch between cooling and preheating modes based on the PCM liquid fraction and cell temperature distribution.