The rapid expansion of electric vehicles (EVs) and renewable energy storage systems has placed the battery pack at the center of technological advancement. While energy density and cycle life remain critical metrics, the safety and reliability of the EV battery pack under diverse environmental conditions have become paramount. Temperature is a decisive factor influencing battery state, longevity, and safety. Elevated temperatures can lead to overheating, accelerated capacity fade, increased internal resistance, and potentially catastrophic thermal runaway. Conversely, low temperatures slow down electrochemical reaction kinetics, reducing available capacity, impairing charge/discharge efficiency, and degrading overall performance. Therefore, enhancing the thermal insulation performance of the EV battery pack under extreme temperature conditions is a vital research direction to ensure stable operation.
Module-less or cell-to-pack (CTP) battery pack architectures are gaining significant attention due to their structural simplicity, reduced weight, and potentially higher volumetric energy density. Unlike traditional modular designs, the thermal conduction paths within a module-less EV battery pack are more direct but also more complex, making uniform temperature management and effective insulation crucial. This paper focuses on the design and performance analysis of the thermal insulation system for a module-less EV battery pack. By analyzing its structural characteristics and their impact on heat transfer, we establish a thermal model to simulate the pack’s temperature evolution under high and low ambient conditions. Experimental validation is conducted to verify the design’s reliability. This work aims to provide a practical and effective design framework for improving the insulation performance of next-generation EV battery packs.
Theoretical Foundations of Thermal Insulation
The thermal management of an EV battery pack, particularly its insulation, is fundamentally governed by the principles of heat transfer: conduction, convection, and radiation.
Heat Conduction
Heat conduction is the transfer of thermal energy through a material via microscopic particle collisions (e.g., molecules, atoms, electrons). In insulation design for an EV battery pack, selecting materials with low thermal conductivity (k) is essential. Materials like polyurethane foam, aerogel, or vacuum insulation panels (VIPs) create a high thermal resistance barrier, minimizing heat flow from the pack’s interior to the colder exterior (or vice versa). The rate of conductive heat transfer through a material layer is described by Fourier’s Law:
$$ Q = -k A \frac{dt}{dx} $$
Where \( Q \) is the heat transfer rate (W), \( k \) is the thermal conductivity (W/(m·K)), \( A \) is the cross-sectional area perpendicular to the heat flow (m²), and \( \frac{dt}{dx} \) is the temperature gradient (K/m). The negative sign indicates heat flows from high to low temperature. Minimizing \( k \) directly reduces \( Q \).
Heat Convection
Heat convection involves the transfer of thermal energy between a surface and a moving fluid (air or liquid). Preventing or managing air movement around and inside the EV battery pack enclosure is critical. Sealing the pack and using insulation materials that also act as air barriers can significantly reduce convective heat loss or gain. Convective heat transfer is commonly modeled using Newton’s Law of Cooling:
$$ \Phi = h A \Delta T $$
Where \( \Phi \) is the convective heat flow (W), \( h \) is the convective heat transfer coefficient (W/(m²·K)), \( A \) is the surface area (m²), and \( \Delta T \) is the temperature difference between the surface and the fluid (K). The value of \( h \) depends on fluid properties, flow velocity, and surface geometry.
Thermal Radiation
Thermal radiation is energy emitted by matter in the form of electromagnetic waves due to its temperature. All surfaces of the EV battery pack radiate heat. Using reflective materials (e.g., aluminum foil laminated on insulation) can effectively reflect radiant heat back into the pack or away from it, reducing net radiative exchange. The power emitted by a surface is given by the Stefan-Boltzmann Law:
$$ E = \epsilon \sigma A T^4 $$
Where \( E \) is the radiant power (W), \( \epsilon \) is the emissivity of the surface (a dimensionless number between 0 and 1), \( \sigma \) is the Stefan-Boltzmann constant (\( 5.67 \times 10^{-8} \, \text{W}/(\text{m}^2 \cdot \text{K}^4) \)), \( A \) is the surface area (m²), and \( T \) is the absolute surface temperature (K). Low-emissivity surfaces (highly reflective) have a small \( \epsilon \), reducing radiative heat loss.
Energy Conservation and Thermal Diffusion
For transient thermal analysis of the EV battery pack insulation system, the energy conservation principle is applied. Assuming constant thermal properties and no internal heat generation within the insulation materials themselves, the three-dimensional, unsteady heat conduction equation is:
$$ \frac{\partial T}{\partial \tau} = \alpha \left( \frac{\partial^2 T}{\partial x^2} + \frac{\partial^2 T}{\partial y^2} + \frac{\partial^2 T}{\partial z^2} \right) $$
Where \( \tau \) is time (s), \( T \) is temperature (K or °C), and \( \alpha \) is the thermal diffusivity (m²/s), defined as:
$$ \alpha = \frac{k}{\rho c_p} $$
Here, \( \rho \) is density (kg/m³) and \( c_p \) is specific heat capacity (J/(kg·K)). While insulation material selection often focuses solely on low thermal conductivity (\( k \)), the thermal diffusivity (\( \alpha \)) provides a more holistic view. A low \( \alpha \) indicates the material not only conducts heat slowly but also responds sluggishly to temperature changes, which is ideal for insulation. For conductive thermal interface materials within the pack, a high \( \alpha \) is desirable to quickly equalize temperatures. This comprehensive material selection strategy enhances the overall thermal management efficacy of the EV battery pack.
Insulation Design for a Module-less EV Battery Pack
Insulation Layer Design Strategy
The insulation layer is a critical subsystem within the EV battery pack. An effective design stabilizes cell temperature across operating environments, thereby enhancing performance, life, and safety. The design and selection process focuses on four key aspects:
- Material Selection: Use high-performance insulation materials with low thermal conductivity. Incorporate reflective layers to mitigate radiative heat transfer. A comparison of common materials is shown in Table 1.
- Material Thickness: For a given material, increasing thickness linearly increases the thermal resistance (\( R_{th} = thickness / k \)), improving insulation performance, albeit with trade-offs in weight and volume.
- Structural Configuration: Implement multi-layer or composite structures to optimize overall thermal resistance and mechanical integrity. Ensure the insulation layer forms a continuous, sealed envelope to minimize air gaps and convective loops.
- Integration with Thermal Management System (TMS): Embed temperature sensors within or adjacent to the insulation for real-time monitoring. In cold climates, design may incorporate heating elements (e.g., PTC heaters) beneath the insulation to actively warm the cells.
| Material | Density (kg/m³) | Thermal Conductivity, k (W/(m·K)) | Key Characteristics |
|---|---|---|---|
| Aerogel Blanket | ~150-200 | 0.015 – 0.025 | Excellent insulation, very low density, flexible. |
| Polyurethane Foam (Rigid) | 30-60 | 0.020 – 0.030 | Good insulation, can be molded, low cost. |
| Vacuum Insulation Panel (VIP) | ~200 | 0.004 – 0.008 | Superior insulation, fragile, sensitive to puncture. |
| Mineral Wool / Rock Wool | 40-200 | 0.035 – 0.045 | Fire-resistant, good acoustic properties, higher k. |
| Elastomeric Foam (Rubber) | 50-80 | 0.035 – 0.045 | Flexible, moisture resistant, easy to install. |
Based on the comparison in Table 1, aerogel composite blankets offer an outstanding balance of extremely low thermal conductivity, flexibility, and fire resistance, making them a premier choice for high-performance insulation in an EV battery pack. For this study, an aerogel blanket is selected as the primary insulation material.
Module-less EV Battery Pack Structural Design
The designed module-less EV battery pack is illustrated in the figure above. The key components are:
- Cell Stacks: 104 prismatic cells are arranged into 8 stacks, each containing 13 cells. Cells within a stack are held together by end plates and side brackets.
- Inter-cell Insulation: Thin (e.g., 2 mm) sheets of insulating material (e.g., mica or ceramic paper) are placed between adjacent cells within a stack to mitigate thermal runaway propagation.
- Thermal Interface Material (TIM): A layer of thermally conductive structural adhesive (e.g., silicone-based, ~2 mm thick) is applied between the bottom of the cell stacks and the cold plate to minimize contact thermal resistance and facilitate cooling during operation.
- Cooling Plate: An aluminum liquid cold plate is located at the bottom of the pack enclosure, integrated with the vehicle’s coolant loop.
- Primary Insulation Layer: Aerogel blanket insulation is adhered to the inner surfaces of the upper enclosure cover and the lower tray (side walls and bottom), creating a continuous thermal barrier between the cells and the external environment.
- Enclosure: A structural upper cover and lower tray (housing) provide mechanical protection and environmental sealing.
For analysis simplification, the following assumptions are made: (1) Heat transfer via radiation is neglected compared to conduction and convection for this insulation study. (2) The enclosure walls are treated as one-dimensional conductive paths in the thermal model. Heat transfer from the pack occurs via: (a) Conduction from cells through the TIM to the cold plate/base, then convection to the ambient air, and (b) Conduction/convection through the internal air to the top cover, then conduction through the insulation and convection to ambient.
Simulation Model Development and Parameter Setting
Model Establishment
A 3D model of the module-less EV battery pack was created using CATIA. For computational efficiency in the insulation-focused simulation, components with negligible impact on overall thermal resistance (e.g., small brackets, bolts) were simplified. The model was imported into Siemens STAR-CCM+ for meshing and analysis. A polyhedral mesh was generated, providing a good balance of accuracy and computational cost. The inner surfaces of the enclosure, lined with the aerogel insulation, are modeled with a convective boundary condition representing the heat exchange with the internal pack air. External surfaces have a convective boundary condition with the ambient environment. Radiation heat transfer is not activated for this insulation performance study.
Physical Property Parameters
The lithium-ion cell is a multi-layer composite (anode, separator, cathode, current collectors, etc.), resulting in anisotropic thermal properties. The effective thermal conductivity differs in the in-plane (x, y) and through-plane (z) directions. The effective properties are calculated using a volume-weighting method.
Through-plane (z-direction, series arrangement of layers) thermal conductivity:
$$ \lambda_z = \frac{\sum L_i}{\sum (L_i / \lambda_i)} $$
In-plane (x, y-direction, parallel arrangement) thermal conductivity:
$$ \lambda_{x,y} = \frac{\sum (\lambda_i L_i)}{\sum L_i} $$
Where \( L_i \) is the thickness of layer \( i \), and \( \lambda_i \) is its thermal conductivity.
The average specific heat capacity of the cell is calculated by mass weighting:
$$ c_{p,cell} = \frac{\sum (c_{p,i} m_i)}{m_{cell}} $$
Where \( c_{p,i} \) and \( m_i \) are the specific heat and mass of constituent \( i \), and \( m_{cell} \) is the total cell mass.
The average density is simply:
$$ \rho_{cell} = \frac{m_{cell}}{V_{cell}} $$
Based on these formulas and constituent material data, the cell and other component properties are derived, as summarized in Table 2. The cold plate is aluminum, coolant is a 50% ethylene glycol-water mixture, and the TIM is a silicone-based gap filler.
| Component / Material | Density, ρ (kg/m³) | Specific Heat, cp (J/(kg·K)) | Thermal Conductivity, λ (W/(m·K)) |
|---|---|---|---|
| Lithium-ion Cell | 2345 | 980 | λx=1.21, λy=λz=17.45 |
| Cold Plate (Aluminum) | 2702 | 903 | 237 |
| Coolant (50% EG) | 1071 | 3300 | 0.384 |
| TIM (Silicone) | 1200 | 1240 | 0.90 |
| Insulation (Aerogel) | 23 | 1457 | 0.013 |
| Enclosure (Steel) | 7850 | 434 | 60.5 |
Model Validation under Discharge
To establish confidence in the simulation model, a baseline validation was performed under a 1C constant-current discharge at a 25°C ambient temperature. The test EV battery pack (with insulation installed) was preconditioned and charged to 100% State of Charge (SOC). It was then discharged at 1C until the cutoff voltage. Temperature was monitored at the central upper surface of selected cells using embedded thermocouples. The experimental results showed a maximum cell temperature rise to 42°C and a minimum of 38°C after 3600s, with a maximum delta-T of 4°C.
The simulation was set up with identical conditions: initial cell temperature at 25°C, ambient at 25°C, and a constant heat generation rate corresponding to 1C discharge (calculated from cell impedance and current). The simulated temperatures after 3600s showed a maximum of 41.3°C and a minimum of 39.7°C, resulting in a delta-T of 1.6°C.
| Temperature Metric | Experiment | Simulation | Error |
|---|---|---|---|
| Maximum Cell Temperature | 42.0 °C | 41.3 °C | -0.7 °C |
| Minimum Cell Temperature | 38.0 °C | 39.7 °C | +1.7 °C |
| Maximum Pack Delta-T | 4.0 °C | 1.6 °C | – |
The error between simulated and experimental cell temperatures is less than 2°C, and both show acceptable temperature uniformity (delta-T < 5°C). This validates the model’s accuracy in capturing the dominant heat transfer mechanisms within the EV battery pack and provides a solid foundation for the insulation performance analysis under static conditions.
Low-Temperature and High-Temperature Soak Tests
Experimental Setup
The test equipment included a battery cycler (NEEF-400-V001), a thermal chamber (GMS HSL/G-04) capable of -70°C to +150°C, a data acquisition system (e.g., Agilent 34972A) and K-type thermocouples. The insulated EV battery pack was placed inside the chamber, connected to the cycler for preconditioning, and monitored via the DAQ system.
Low-Temperature (-20°C) Soak Test
Procedure: 1) The pack was stabilized at a uniform 25°C in the chamber. 2) The chamber temperature was set to -20°C. 3) The pack was soaked for 6 hours without any active thermal management (cooling/heating). Cell temperatures were logged continuously. The target was to maintain the minimum cell temperature above 0°C after the 6-hour soak.
Results & Analysis: The temperature profiles of the maximum and minimum temperature cells are plotted. The pack’s initial temperature was 25°C. After 6 hours (21,600 seconds) at -20°C, the minimum cell temperature was approximately 3°C. The average cooldown rate can be estimated as:
$$ \text{Cooldown Rate} \approx \frac{25^\circ\text{C} – 3^\circ\text{C}}{6\,\text{h}} \approx 3.67\,^\circ\text{C/h} $$
This relatively slow cooldown rate demonstrates the effectiveness of the aerogel insulation. The EV battery pack successfully maintained cell temperatures above 0°C, which is critical for preventing lithium plating and preserving performance in cold climates.
Simulation Correlation: A transient simulation was run with an initial pack temperature of 25°C and an ambient boundary condition of -20°C (with an external convective coefficient of 5 W/(m²·K)). The simulated temperature distribution after 6 hours showed a similar gradient, with the core cells being warmest. The simulated minimum temperature after 6h was approximately 4.5°C. The correlation error with the experiment was within 1.5°C, confirming the model’s predictive capability for low-temperature insulation performance.
High-Temperature (+55°C) Soak Test
Procedure: 1) The pack was again stabilized at 25°C. 2) The chamber temperature was set to +55°C. 3) The pack was soaked for 6 hours. Cell temperatures were monitored. A typical target is to keep the maximum cell temperature below a safe limit (e.g., 45-50°C) to avoid accelerated aging.
Results & Analysis: The temperature profiles show the pack heating up from 25°C. After 6 hours at 55°C, the maximum cell temperature reached approximately 42°C. The average warm-up rate is:
$$ \text{Warm-up Rate} \approx \frac{42^\circ\text{C} – 25^\circ\text{C}}{6\,\text{h}} \approx 2.83\,^\circ\text{C/h} $$
This rate is even lower than the cooldown rate, highlighting the insulation’s effectiveness in a hot ambient environment. It significantly slows the heat ingress, keeping cells substantially cooler (by ~13°C) than the external ambient. This reduces thermal stress on the cells and lessens the burden on the active cooling system when the vehicle is parked.
Simulation Correlation: The high-temperature soak simulation (initial 25°C, ambient 55°C) yielded a post-6h maximum cell temperature of 40.3°C. The temperature contour revealed an interesting pattern: unlike in the cold soak where core cells were warmest, in the hot soak, cells near the insulated walls were slightly warmer due to heat ingress, while those in the core were slightly cooler. The simulation-experiment error was again within 2°C.
| Test Condition | Duration | Ambient Temp. | Initial Cell Temp. | Final Min. Cell Temp. | Final Max. Cell Temp. | Avg. Temp. Change Rate | Performance Assessment |
|---|---|---|---|---|---|---|---|
| Low-Temp Soak | 6 hours | -20 °C | 25 °C | ~3 °C | ~15 °C | ~3.67 °C/h (cooling) | Pass. Cells > 0°C. |
| High-Temp Soak | 6 hours | +55 °C | 25 °C | ~38 °C | ~42 °C | ~2.83 °C/h (heating) | Pass. Cells << 55°C ambient. |
Conclusion
This study presented a comprehensive design and performance analysis of the thermal insulation system for a module-less EV battery pack. The design utilized an aerogel blanket applied to the inner surfaces of the pack enclosure. Through coupled experimental testing and finite element simulation, the insulation system’s performance was rigorously evaluated.
The key finding is that the designed insulation significantly decouples the internal cell temperature from harsh external environments. In a -20°C ambient, the pack’s cooldown rate was approximately 3.67°C/h, successfully preserving cell temperatures above 0°C for a 6-hour soak. In a +55°C ambient, the warm-up rate was even lower at ~2.83°C/h, maintaining cells over 10°C cooler than the environment. The simulation model demonstrated good correlation with experimental data (errors < 2°C), validating its utility as a design tool. This confirms that the proposed insulation structure for the EV battery pack effectively meets thermal protection requirements, enhancing performance and safety under extreme temperature conditions.
Future work could explore the development of multifunctional composite materials that combine high thermal conductivity for in-pack cell-to-cell heat spreading with excellent insulating properties at the pack boundary. Furthermore, integrating Phase Change Materials (PCMs) within the EV battery pack could be investigated to provide additional passive temperature stabilization, especially during transient high-power events or in environments with significant diurnal temperature swings, further optimizing the thermal resilience of the energy storage system.