In this research, I focus on the cooling performance of a single‑phase immersion‑cooled energy storage battery unit module. Energy storage battery systems are critical for integrating renewable energy sources, and thermal management is essential to ensure safe operation and long cycle life. I employ Computational Fluid Dynamics (CFD) simulations to predict the temperature field within the module, and then validate the numerical results through physical experiments. The study demonstrates that a flow rate of 3 L · min⁻¹ per module satisfies the design requirements: a maximum cell temperature below 35 °C and a temperature difference among cells under 3 °C. The simulation and experimental results show good agreement, confirming the accuracy of the proposed simulation methodology and providing a reliable reference for future immersion‑cooled energy storage battery designs.
Introduction
The rapid expansion of renewable energy sources such as solar and wind power has intensified the need for efficient and reliable energy storage battery systems. Lithium‑iron‑phosphate (LFP) batteries are widely adopted in large‑scale energy storage battery applications due to their high cycle life, energy density, and thermal stability. However, thermal runaway events caused by inadequate cooling have led to severe accidents in recent years. Consequently, battery thermal management has become a non‑negotiable aspect of energy storage battery design. Air‑cooling systems are gradually being replaced by liquid‑cooling technologies because of the latter’s superior heat transfer efficiency and temperature uniformity. Among liquid‑cooling approaches, direct immersion cooling offers the highest potential by eliminating the thermal resistance of cold plates. In this work, I investigate the cooling performance of a modular immersion‑cooled energy storage battery unit. I use CFD to simulate the temperature distribution under different flow rates and validate the results with experimental data from a prototype. The goal is to establish a reliable simulation methodology that can guide the development of immersion‑cooled energy storage battery systems.
Modular Immersion Energy Storage Battery System
The modular immersion energy storage battery system consists of multiple immersion‑cooled battery unit modules, a circulating pump, a plate heat exchanger, and an external cooling unit. Each immersion battery unit module contains the battery cells, a dielectric cooling fluid, and flow channels. The batteries are fully submerged in the coolant, allowing direct heat transfer from the cell surfaces to the liquid. The heated coolant is then pumped to a plate heat exchanger where the heat is rejected to an external loop. The cooled fluid returns to the module for continuous operation. This modular design facilitates easy installation, maintenance, and scalability. For this study, I focus on a single module that houses two 1P26S battery strings (each string has 26 cells in series) with a total of 52 cells. The cooling flow path is designed in parallel for the two strings to ensure uniform distribution. The geometry and material properties of the cells are listed in Table 1.
| Parameter | Value |
|---|---|
| Cell type | 280 Ah prismatic LFP |
| Dimensions (L × W × H) | 164 mm × 72 mm × 194 mm |
| Heat generation rate (0.5 C) | 16.5 W per cell |
| Thermal conductivity (X, Z direction) | 14 W m⁻¹ K⁻¹ |
| Thermal conductivity (Y direction) | 2.5 W m⁻¹ K⁻¹ |
| Gasket thermal conductivity (between cells) | 0.05 W m⁻¹ K⁻¹ |
| Coolant inlet temperature | 20 °C |
Numerical Simulation Methodology
Governing Equations
The flow and heat transfer in the immersion‑cooled energy storage battery module are governed by the three‑dimensional, incompressible Navier‑Stokes equations with energy transport. The continuity, momentum, and energy equations are expressed as follows:
$$
\frac{\partial \rho}{\partial t} + \nabla \cdot (\rho \mathbf{v}) = 0
$$
$$
\frac{\partial \mathbf{v}}{\partial t} + (\mathbf{v} \cdot \nabla) \mathbf{v} = -\frac{1}{\rho} \nabla p + \nu \nabla^{2} \mathbf{v} + \mathbf{f}
$$
$$
\frac{\partial (\rho T)}{\partial t} + \nabla \cdot (\rho \mathbf{v} T) = \nabla \cdot \left( \frac{k}{c_p} \nabla T \right) + S_h + \Phi
$$
where \(\rho\) is fluid density, \(\mathbf{v}\) velocity vector, \(p\) pressure, \(\nu\) kinematic viscosity, \(\mathbf{f}\) body force, \(T\) temperature, \(k\) thermal conductivity, \(c_p\) specific heat, \(S_h\) volumetric heat source, and \(\Phi\) viscous dissipation. I solve these equations using the finite‑volume method with appropriate boundary conditions.
Simulation Model and Mesh
To reduce computational cost, I simplify each battery cell as a uniform heat‑generating solid with anisotropic thermal conductivity. The simulation domain comprises a single 1P26S battery string (26 cells) with the surrounding fluid region and flow channels. The total mesh count is approximately 2.14 million elements, with refined meshes near the cell surfaces and in the narrow flow gaps. Figure 1 (not shown) illustrates the computational grid.
Boundary Conditions
The inlet coolant temperature is fixed at 20 °C. I consider two flow rates: 2.5 L · min⁻¹ and 3 L · min⁻¹ for the single module, corresponding to 5 L · min⁻¹ and 6 L · min⁻¹ for the entire unit module (two strings) respectively. The heat generation per cell is 16.5 W under 0.5 C rate. The required flow rate is calculated based on the allowable temperature rise of the coolant:
$$
P = \rho \, c_p \, V \, \Delta T
$$
where \(P\) is total heat power of the module (26 × 16.5 W = 429 W), \(V\) is volumetric flow rate, and \(\Delta T\) is the temperature rise across the module. Setting \(\Delta T \le 5\,^{\circ}\mathrm{C}\) yields a minimum flow rate of about 2.77 L · min⁻¹. Hence I evaluate both 2.5 and 3 L · min⁻¹.
Simulation Results and Analysis
Steady‑State Results at 2.5 L · min⁻¹
First, I perform steady‑state simulations for the single module at 2.5 L · min⁻¹. The maximum cell surface temperature reaches 36.9 °C, which exceeds the design limit of 35 °C. The maximum temperature difference among cells is 3.4 °C, also above the 3 °C requirement. The hottest cells are located near the outlet side, where the coolant has already absorbed significant heat. Table 2 summarizes the key steady‑state results for both flow rates.
| Flow rate (L · min⁻¹) | Max cell temperature (°C) | Max temperature difference (°C) | Design compliance |
|---|---|---|---|
| 2.5 | 36.9 | 3.4 | No |
| 3.0 | 35.7 | 3.2 | No |
Even at 3 L · min⁻¹, the steady‑state results show a maximum temperature of 35.7 °C and a difference of 3.2 °C, still marginally above the targets. However, real energy storage battery systems operate in cycles (charge, rest, discharge), and transient simulations often yield lower peak temperatures because heat accumulation is limited. Therefore, I proceed with transient analysis for the 3 L · min⁻¹ case.
Transient Simulation at 3 L · min⁻¹
I simulate a full cycle: 0.5 C charge for 2 h, rest for 30 min, and 0.5 C discharge for 2 h. The inflow temperature remains 20 °C. The temperature distributions at the end of charge, rest, and discharge are evaluated. Key results are listed in Table 3.
| Phase | Max cell temperature (°C) | Max temperature difference (°C) |
|---|---|---|
| End of charge | 31.8 | 2.1 |
| End of rest | 28.6 | 1.8 |
| End of discharge | 33.9 | 2.9 |
The transient results reveal that the maximum temperature (33.9 °C) occurs at the end of discharge and remains below 35 °C. The maximum temperature difference is 2.9 °C, which is under 3 °C. Hence, a flow rate of 3 L · min⁻¹ per module (6 L · min⁻¹ per unit module) satisfies the design requirements for a realistic charge‑discharge cycle. The simulation therefore confirms that the proposed energy storage battery module cooling structure is effective.
Experimental Validation
Experimental Setup
To verify the simulation accuracy, I construct a prototype of the immersion‑cooled energy storage battery unit module with the same geometry and flow configuration. The test rig includes a coolant circulation system, a chiller to maintain inlet temperature at 20 °C, a battery cycler for charge/discharge control, and thermocouples attached to the cell tabs (terminals) to monitor temperatures. The module is subjected to multiple 0.5 C charge‑discharge cycles identical to the simulation schedule. Data from the fourth cycle is used for comparison.
Experimental Results
The measured maximum cell temperature during the entire experiment is 33 °C, occurring near the end of charge or discharge. The maximum temperature difference among the 52 cells is 2.7 °C. These values are close to the simulation predictions (33.9 °C and 2.9 °C respectively). The slight discrepancies can be attributed to uncertainties in material properties, manufacturing tolerances, and heat loss to the ambient. Nonetheless, the overall agreement confirms the reliability of the CFD approach for predicting the thermal behavior of immersion‑cooled energy storage battery modules. Table 4 compares the key experimental and simulation data.
| Parameter | Simulation | Experiment |
|---|---|---|
| Maximum cell temperature (°C) | 33.9 | 33.0 |
| Maximum temperature difference (°C) | 2.9 | 2.7 |
| Flow rate per module (L · min⁻¹) | 3.0 | 3.0 |
| Inlet coolant temperature (°C) | 20 | 20 |
Conclusion
In this study, I have systematically evaluated the cooling performance of an immersion‑cooled energy storage battery unit module using both CFD simulation and experimental testing. The key findings are as follows:
- A flow rate of 2.5 L · min⁻¹ per module results in steady‑state cell temperatures exceeding the 35 °C limit and temperature differences above 3 °C, making it insufficient for safe operation.
- At 3 L · min⁻¹ (6 L · min⁻¹ per unit module), the transient simulation shows that the maximum cell temperature reaches 33.9 °C and the maximum temperature difference is 2.9 °C during a standard 0.5 C cycle, both within the design criteria.
- Experimental results from a prototype confirm the simulation: the measured maximum temperature is 33 °C and the maximum difference is 2.7 °C, with good overall agreement.
- The validated CFD methodology provides a reliable tool for the design and optimization of immersion‑cooled energy storage battery systems, enabling future advancements in thermal management.
The established simulation approach can be extended to larger energy storage battery arrays and different operating conditions, facilitating the development of safer and more efficient energy storage battery solutions.