Abstract
Energy storage battery is critical components in modern power systems, particularly lithium-ion batteries, which are widely used due to their high energy density and efficiency. However, thermal management remains a significant challenge, as excessive temperatures can lead to thermal runaway and safety hazards. This study quantitatively compares the heat transfer characteristics of air-cooled and liquid-cooled energy storage battery modules using numerical simulations. Key performance metrics, including heat transfer efficiency, flow resistance, comprehensive thermal-fluid performance, and environmental adaptability, are analyzed. Results demonstrate that liquid cooling exhibits superior temperature uniformity (0.5°C inter-cell) and adaptability to ambient temperature fluctuations, while air cooling shows advantages in specific scenarios with low cooling medium temperature differences. The findings provide critical insights for optimizing thermal management systems in energy storage applications.
1. Introduction
The rapid development of renewable energy systems has intensified the demand for efficient energy storage solutions. Lithium-ion energy storage battery dominate this sector due to their high energy density, long cycle life, and fast charge-discharge rates. However, their performance and safety are highly sensitive to temperature variations. Elevated temperatures can trigger thermal runaway, while low temperatures reduce capacity and lifespan. Effective thermal management systems (TMS) are therefore essential to maintain optimal operating conditions.
Current TMS technologies include air cooling, liquid cooling, phase-change materials, and hybrid approaches. Among these, air and liquid cooling are the most mature and widely adopted. Air cooling offers simplicity and cost-effectiveness but suffers from low heat transfer coefficients. Liquid cooling provides superior cooling efficiency but involves higher complexity and maintenance costs. This study focuses on comparing these two methods for energy storage battery modules, emphasizing quantitative metrics such as temperature uniformity, flow resistance, and environmental adaptability.
2. Methodology
2.1 Numerical Model Setup
A 50 Ah battery module comprising 26 cells arranged in two columns (13 cells each) was simulated. Key parameters include:
- Cell dimensions: 205 mm × 174 mm × 72 mm
- Heat generation: 31.62 W (charging) and 28.56 W (discharging) at 1 C rate
2.1.1 Air-Cooled Module Design
Airflow enters through a lower plenum, distributes via parallel channels between cells, and exits through an upper plenum (Figure 2 in original text). Key design parameters:
- Inlet/outlet dimensions: 408 mm × 20 mm
- Inter-cell channel width: 10 mm
2.1.2 Liquid-Cooled Module Design
Indirect liquid cooling with parallel straight channels was modeled (Figure 3 in original text). Key parameters:
- Coolant: 50% ethylene glycol-water mixture
- Channel thickness: 3.5 mm
- Contact area per cell: 216,000 mm²
2.2 Governing Equations
The following equations were solved using the finite volume method with the SIMPLE algorithm:
- Continuity Equation:∇⋅(ρu)=0∇⋅(ρu)=0
- Momentum Equation:ρu⋅∇u=−∇P+μ∇2uρu⋅∇u=−∇P+μ∇2u
- Energy Equation for Fluid:ρcpu⋅∇T=∇⋅(λ∇T)ρcpu⋅∇T=∇⋅(λ∇T)
- Energy Equation for Battery:ρbcb∂T∂t=λx∂2T∂x2+λy∂2T∂y2+λz∂2T∂z2+qbρbcb∂t∂T=λx∂x2∂2T+λy∂y2∂2T+λz∂z2∂2T+qb
- Standard k-ε Turbulence Model:∂(ρk)∂t+∇⋅(ρku)=∇⋅[(μ+μtσk)∇k]+Gk−ρϵ∂t∂(ρk)+∇⋅(ρku)=∇⋅[(μ+σkμt)∇k]+Gk−ρϵ∂(ρϵ)∂t+∇⋅(ρϵu)=∇⋅[(μ+μtσϵ)∇ϵ]+C1ϵϵkGk−C2ϵρϵ2k∂t∂(ρϵ)+∇⋅(ρϵu)=∇⋅[(μ+σϵμt)∇ϵ]+C1ϵkϵGk−C2ϵρkϵ2
2.3 Boundary Conditions and Material Properties
Key parameters include:
- Ambient temperature: 20°C
- Coolant inlet velocity: Calculated based on temperature difference (ΔT)
- Battery heat generation: 822.12 W (total)
Material properties are summarized in Table 1.
Table 1: Material Properties
| Material | Density (kg/m³) | Viscosity (mPa·s) | Specific Heat (J/kg·K) | Thermal Conductivity (W/m·K) |
|---|---|---|---|---|
| Air | 1.205 | 0.0183 | 1013 | 0.0267 |
| Coolant | 1071.1 | 3.94 | 3300 | 0.384 |
| Battery | 2230 | — | 982 | λ_x=23.88, λ_y=λ_z=0.65 |
| Aluminum Alloy | 2680 | — | 947 | 156 |
3. Results and Discussion
3.1 Heat Transfer Performance
The relationship between cooling medium flow rate (QvQv) and temperature difference (ΔTfΔTf) is given by:qb=QvρcpΔTfqb=QvρcpΔTf
Table 2: Cooling Medium Flow Rates
| ΔT_f (°C) | Air Flow (m³/h) | Liquid Flow (L/h) |
|---|---|---|
| 1 | 39,873 | 13.77 |
| 2 | 19,937 | 6.885 |
| 4 | 9,968 | 3.443 |
| 6 | 6,646 | 2.295 |
| 8 | 4,984 | 1.721 |
| 10 | 3,987 | 1.377 |
Key findings:
- Temperature Uniformity: Liquid cooling achieved a maximum inter-cell of 0.5°C, compared to 6.1°C for air cooling.
- Heat Transfer Factor (JJ):J=NuRe⋅Pr1/3J=Re⋅Pr1/3NuLiquid cooling (J=9.67×10−3J=9.67×10−3) outperformed air cooling (J=2.91×10−3J=2.91×10−3) by 3.32×.
3.2 Flow Resistance Performance
The pressure drop (ΔPΔP) and resistance factor (FF) were analyzed:F=2ΔPρu2F=ρu22ΔP
- Liquid cooling exhibited 5.22–17.62× higher FF than air cooling.
- Pressure drop decreased nonlinearly with increasing ΔTfΔTf (Figure 10 in original text).
3.3 Comprehensive Thermal-Fluid Performance
The θ-factor (θ=J/Fθ=J/F) was used to evaluate combined performance:
- Liquid cooling showed 1.27–1.71× higher θ than air cooling.
- Performance advantage increased with higher coolant flow rates.
3.4 Environmental Adaptability
At ΔTf=6°CΔTf=6°C, liquid cooling demonstrated superior stability under ambient temperature (TaTa) variations:
Table 3: Temperature Sensitivity to TaTa
| Metric | Air Cooling | Liquid Cooling |
|---|---|---|
| TmaxTmax increase (0–30°C) | 4.25°C | 1.06°C |
| TminTmin increase (0–30°C) | 8.34°C | 0.03°C |
| ΔTmaxΔTmax variation | +5.17°C | +1.03°C |
4. Conclusion
- Heat Transfer: Liquid cooling excels in scenarios requiring high ΔTfΔTf (>1.76°C), while air cooling is preferable for low ΔTfΔTf applications.
- Flow Resistance: Liquid cooling incurs higher pressure drops, necessitating optimized分流 structures.
- Comprehensive Performance: θ-factor analysis confirms liquid cooling’s superiority, especially at elevated flow rates.
- Environmental Adaptability: Liquid cooling exhibits minimal temperature fluctuations under varying ambient conditions, making it ideal for dynamic environments.
These insights advance the design of thermal management systems for energy storage battery, ensuring safety and efficiency in renewable energy applications.