Thermal management stands as a critical challenge for energy storage battery systems, especially under high-rate charging and discharging conditions. Efficient heat dissipation is paramount to maintaining performance, ensuring safety, and extending the cycle life of energy storage battery packs. This work focuses on developing and evaluating liquid cooling strategies for a high-capacity lithium iron phosphate (LiFePO4) energy storage battery module under a 1C operational regime. By establishing a coupled electric-thermal-fluid simulation model that accounts for heat generation from both the battery cells and the interconnecting busbars, we systematically analyze the impact of various cold plate layout configurations and coolant flow rates on the module’s temperature characteristics. The primary objectives are to identify cooling schemes capable of controlling the maximum temperature rise and improving temperature uniformity within the module, which are essential for the reliable operation of high-rate energy storage battery systems.
Methodology: Coupled Model Development
The core of this investigation is a multi-physics simulation model that integrates electrical, thermal, and fluid dynamics phenomena. The model geometry comprises seven prismatic LiFePO4 cells (nominal voltage: 3.2 V, capacity: 280 Ah), aluminum busbars, liquid cold plates, and connecting tubes. To explore effective cooling strategies, cold plates are arranged on different surfaces of the battery module: the bottom surface, the large side surfaces (referred to as “large surfaces”), and the smaller side surfaces (referred to as “side surfaces”). A total of nine distinct cooling schemes are defined, as summarized in Table 1. Thermal interface material is assumed to fill the gaps between the cold plates and the battery cells to facilitate heat transfer.
| Scheme ID | Scheme Name | Description |
|---|---|---|
| 1 | Bottom | One cold plate on the bottom surface. |
| 2 | Single Large Surface | Four large-surface cold plates arranged alternately and connected in series. |
| 3 | Single Large Surface + Bottom | Scheme 2 plus one bottom cold plate. |
| 4 | Double Large Surface | Eight large-surface cold plates (on both sides) connected in series. |
| 5 | Double Large Surface + Bottom | Scheme 4 plus one bottom cold plate. |
| 6 | Side Series | Two side-surface cold plates connected in series. |
| 7 | Side Series + Bottom | Scheme 6 plus one bottom cold plate. |
| 8 | Side Parallel | Two side-surface cold plates connected in parallel. |
| 9 | Side Parallel + Bottom | Scheme 8 plus one bottom cold plate. |
Mathematical Formulation of the Coupled Model
The coupled model is built upon the fundamental governing equations for the electric field, heat transfer, and fluid flow.
1. Electrical Field and Busbar Joule Heating: For the steady-state DC current flowing through the busbars, the electric field is governed by:
$$ \nabla \cdot \mathbf{J} = 0 $$
$$ \nabla \times \mathbf{E} = 0 $$
where $\mathbf{J}$ is the current density and $\mathbf{E}$ is the electric field intensity. The resulting Joule heating power density $p$ within the busbars is calculated using the differential form of Joule’s law:
$$ p = \mathbf{J} \cdot \mathbf{E} $$
The total heat generation power $P_{busbar}$ for a busbar is obtained by integrating the power density over its volume $V$:
$$ P_{busbar} = \int_V (\mathbf{J} \cdot \mathbf{E}) dV $$
2. Heat Transfer Analysis: Heat conduction within the solid components (battery, busbars, cold plates) follows Fourier’s law:
$$ \mathbf{q} = -k \nabla T $$
where $\mathbf{q}$ is the heat flux vector, $k$ is the thermal conductivity, and $\nabla T$ is the temperature gradient. Convective heat transfer between the cold plate walls and the coolant is described by Newton’s law of cooling:
$$ q = h \Delta t $$
where $q$ is the convective heat flux, $h$ is the convective heat transfer coefficient, and $\Delta t$ is the temperature difference between the wall and the coolant. Radiation and natural convection to the ambient are neglected in this forced liquid cooling analysis.
3. Fluid Flow and Energy Transport: The coolant flow is assumed to be incompressible and viscous. The governing equations for mass, momentum, and energy conservation are:
Continuity equation: $$ \nabla \cdot \mathbf{v} = 0 $$
Momentum equation (Navier-Stokes): $$ \rho \frac{\partial \mathbf{v}}{\partial t} + \rho (\mathbf{v} \cdot \nabla) \mathbf{v} = -\nabla P + \mu \nabla^2 \mathbf{v} $$
Energy equation: $$ \rho C_p \frac{\partial T}{\partial t} + \nabla \cdot (\rho C_p \mathbf{v} T) = \nabla \cdot (k \nabla T) $$
Here, $\mathbf{v}$ is the fluid velocity vector, $P$ is pressure, $\rho$ is density, $\mu$ is dynamic viscosity, $C_p$ is specific heat capacity, and $T$ is temperature.
Simulation Setup and Material Properties
A steady-state simulation is performed for the 1C operating condition. Each energy storage battery cell is assumed to generate a uniform heat of 33 W. The Joule heating distribution in the busbars is first obtained from an electric field simulation and then imported as a volumetric heat source into the fluid-thermal solver. Key assumptions include: coolant is an incompressible viscous fluid (50% ethylene glycol-water solution), contact resistance between battery terminals and busbars is negligible, and ambient heat loss is not considered. The material properties used in the simulation are listed in Table 2.
| Material/Component | Density (kg/m³) | Specific Heat (J/(kg·K)) | Thermal Conductivity (W/(m·K)) |
|---|---|---|---|
| Energy Storage Battery Cell | 2133 | 964 | k_x=9.04, k_y=3.56, k_z=11.00* |
| Coolant (50% EG-Water) | 1071 | 3300 | 0.384 |
| Thermal Interface Material | 3000 | 1150 | 2.0 |
| Aluminum (Busbars/Cold Plates) | Standard properties for aluminum alloy are applied. |
* The energy storage battery cell is modeled with orthotropic thermal conductivity.
Results and Discussion
Busbar Heat Generation Analysis
The electric field simulation reveals that the current density and consequently the Joule heating power density in the busbars are highly concentrated in the region directly between the two terminal connections. The peripheral areas contribute minimally to current conduction. The calculated total heat generation from all busbars in the module is 12.06 W. This localized heating makes the busbars potential hotspots, underscoring the necessity of including them in the thermal model for an accurate assessment of the energy storage battery module’s thermal state.
Temperature Distribution Characteristics
The temperature distribution for selected cooling schemes (Bottom, Double Large Surface, Double Large Surface+Bottom, Side Series, Side Series+Bottom) is analyzed. For the Bottom-only scheme, temperature increases vertically from the cooled bottom, with the busbars reaching the highest temperature (max rise ~42 K). This scheme is inadequate for high-rate energy storage battery operation. Schemes with large-surface or side-surface cold plates show significantly better performance. The coolant temperature increases along the flow path, leading to a corresponding increase in busbar temperature from the inlet side to the outlet side of the module. The Double Large Surface and Side Series schemes limit the maximum temperature rise to about 14 K. Adding a bottom cold plate to these schemes provides further improvement, reducing the maximum rise to approximately 13 K and 12 K, respectively.
Influence of Coolant Flow Rate
The relationship between the maximum temperature rise of the positive busbars (cells C2 to C6) and the coolant flow rate is investigated for all schemes. A key finding is that increasing the flow rate consistently reduces both the maximum temperature rise ($T_M$) and the temperature rise range ($R_T$, or temperature non-uniformity) across all viable cooling schemes. However, the rate of improvement diminishes with increasing flow. For schemes involving large-surface or side-surface cold plates, the benefit of increasing the flow rate beyond 3 L/min becomes marginal, with reductions in $T_M$ and $R_T$ typically less than 0.6 K and 0.4 K, respectively. This suggests an optimal flow rate range exists for balancing cooling performance against pumping power for the energy storage battery thermal management system.
Comparative Analysis of Cooling Schemes
Excluding the ineffective Bottom-only scheme, the performance of the remaining eight schemes is compared in terms of $T_M$ and $R_T$ versus flow rate. The Single Large Surface scheme consistently shows the highest $T_M$. In contrast, the Double Large Surface and all Side cooling schemes (Series and Parallel) exhibit similar and much better capability in controlling the maximum temperature, maintaining $T_M$ below 11 K at flow rates above 2 L/min.
Regarding temperature uniformity ($R_T$), the schemes employing side-surface cold plates generally outperform those using large-surface cold plates, especially at lower flow rates. This advantage narrows at higher flows, with the difference in $R_T$ becoming less than 0.5 K at 3 L/min.
The effect of adding a bottom cold plate as a supplement varies:
- For the Single Large Surface scheme, adding a bottom plate significantly reduces $T_M$ by over 2 K across all studied flow rates.
- For the Double Large Surface and Side Series schemes, adding a bottom plate reduces $T_M$, but the benefit decreases with increasing flow rate, becoming less than 1 K above 1-2 L/min.
- For temperature uniformity, adding a bottom plate is beneficial for the Single Large Surface, Double Large Surface, and Side Series schemes, but the improvement in $R_T$ also diminishes with higher flow. For the Side Parallel scheme, adding a bottom plate does not improve $R_T$.
These insights are crucial for designing efficient and cost-effective thermal management systems for high-rate energy storage battery modules.
Experimental Validation
To verify the accuracy of the coupled simulation model, experiments were conducted on the energy storage battery module configured with three cooling schemes: Double Large Surface, Side Series, and Side Parallel (including their variants with a bottom plate). The tests were performed under a 1C charge-discharge cycle with the total coolant flow rate for the main cold plates set at 1 L/min. The temperature of the positive busbars was monitored using thermocouples and compared against the simulation predictions.
The comparison shows excellent agreement between simulation and experimental results. The maximum error in predicting the busbar temperature rise is within 0.9 K for the Double Large Surface schemes, within 0.8 K for the Side Series schemes, and within 0.6 K for the Side Parallel schemes. The minor discrepancies can be attributed to model simplifications (e.g., uniform cell heating, neglected natural convection) and experimental uncertainties (e.g., fluctuations in ambient and coolant inlet temperatures). This close validation confirms the reliability of the established electric-thermal-fluid coupled model for analyzing and designing liquid cooling systems for energy storage battery modules.
| Aspect | Key Finding | Implication for Energy Storage Battery Design |
|---|---|---|
| Busbar Heating | Joule heating is concentrated between terminals. | Busbar geometry can be optimized to reduce mass and hotspot risk. |
| Scheme Effectiveness | Double Large Surface & Side cooling schemes control $T_M$ < 11 K. | These schemes are viable for 1C operation of energy storage batteries. |
| Temperature Uniformity | Side cooling schemes generally offer better $R_T$ than large-surface schemes. | Important for balancing cell aging and performance in the energy storage battery pack. |
| Flow Rate Effect | Performance improves with flow but diminishes above ~3 L/min. | Suggests an optimal flow range to minimize pump energy in the energy storage battery system. |
| Supplementary Bottom Cooling | Most beneficial for Single Large Surface scheme; benefit decreases with flow for others. | Cost-benefit of adding a bottom plate should be evaluated based on primary scheme and operating flow. |
Conclusion
This study presents a comprehensive analysis of liquid cooling strategies for high-rate energy storage battery modules based on a developed electric-thermal-fluid coupled simulation model. The model successfully incorporates the effects of heat generation from both the energy storage battery cells and the interconnecting busbars. The main conclusions are:
- The Double Large Surface and Side-surface (Series or Parallel) cold plate arrangements are effective solutions for high-rate energy storage battery modules, capable of limiting the maximum temperature rise to within 11 K under 1C operation, which is essential for maintaining the health and performance of the energy storage battery system.
- Cooling schemes utilizing side-surface cold plates generally provide better temperature uniformity within the energy storage battery module compared to those using large-surface cold plates, particularly at lower coolant flow rates.
- Increasing the coolant flow rate improves both the maximum temperature rise and temperature uniformity, but the gains become insignificant beyond approximately 3 L/min, indicating a point of diminishing returns for the energy storage battery cooling system.
- The utility of adding a supplementary bottom cold plate depends on the primary cooling scheme and the operating flow rate. It offers significant benefit for the Single Large Surface scheme but provides a smaller, flow-dependent improvement for the more effective Double Large Surface and Side Series schemes.
The experimental validation confirms the model’s accuracy, providing confidence in using this approach for the thermal design and optimization of energy storage battery systems. Future work will extend this analysis to higher C-rate operations, incorporate more detailed models of battery internal heat generation, and explore the optimization of cold plate internal channel geometry to further enhance the thermal management of next-generation high-power energy storage battery packs.