In the context of global efforts to combat climate change and reduce pollution, the adoption of electric vehicles has emerged as a critical strategy. As a researcher focused on advancing EV technologies, I have dedicated my work to improving the thermal management systems of power batteries, which are essential for the performance and safety of electric vehicles. The electric vehicle market, particularly in China, is expanding rapidly, and addressing challenges like battery thermal management in low-temperature conditions is paramount. In this study, I designed and evaluated a flat ultra-thin micro heat pipe system for lithium-ion power batteries, specifically targeting the unique demands of China EV applications. This system aims to enhance both heating and cooling efficiency, ensuring optimal battery operation even in harsh environments.
The core of any electric vehicle is its power battery, and lithium-ion batteries are widely used due to their high energy density and long cycle life. However, temperature fluctuations, especially in low-temperature settings, can severely impact battery performance. For instance, temperatures that are too low can increase internal resistance, reduce capacity, and accelerate aging, potentially leading to thermal runaway. My research focuses on integrating phase-change heat pipes into the battery thermal management system. These heat pipes offer advantages like high thermal conductivity, compact structure, and bidirectional heat flow, making them ideal for electric vehicle applications. In this article, I will detail the design of the flat ultra-thin micro heat pipe, the development of a segmented thermal resistance model coupled with a battery thermal model, and the simulation results that demonstrate its effectiveness in various low-temperature scenarios.
To begin, I designed the flat ultra-thin micro heat pipe with a focus on its application in a 3.2 V 50 Ah lithium-ion power battery pack, commonly used in electric vehicles. The heat pipe operates on the principle of phase-change heat transfer, consisting of an evaporator section, a condenser section, and an adiabatic section. The working fluid, chosen after careful consideration, is water due to its suitable properties for low-temperature environments. The selection criteria for the working fluid include a wide temperature range, high latent heat, and compatibility with the copper shell. The heat pipe’s structure includes a sintered copper wick, a wall thickness of 0.16 mm, and a maximum vapor chamber diameter of 5.51 mm, optimized for efficient heat transfer in electric vehicle batteries. The fundamental equation governing the heat pipe’s operation is the capillary pressure condition, expressed as:
$$ \Delta P_c \geq \Delta P_p + \Delta P_l + \Delta P_g $$
where $\Delta P_c$ is the capillary pressure head, $\Delta P_p$ is the pressure drop due to vapor flow, $\Delta P_l$ is the liquid flow pressure drop, and $\Delta P_g$ is the gravitational pressure drop. This ensures continuous fluid circulation, which is crucial for maintaining thermal stability in electric vehicle power batteries. To support this design, I compiled data on various working fluids, as shown in Table 1, which summarizes their temperature ranges and key properties. This table highlights why water is the preferred choice for low-temperature applications in China EV systems, given its boiling point of 100°C and freezing point of 0°C, which align well with typical operating conditions.
| Working Fluid | Temperature Range (°C) | Boiling Point (°C) | Freezing Point (°C) |
|---|---|---|---|
| Ammonia | -60 to 1100 | -33 | -78 |
| Methanol | 10 to 130 | 64 | -98 |
| R113 | -10 to 100 | 48 | -35 |
| Acetone | 0 to 120 | 57 | -95 |
| Mercury | 250 to 650 | 361 | -39 |
| Lithium | 1000 to 1800 | 1340 | 179 |
| Dowtherm A | 150 to 395 | 257 | 12 |
| Sulfur | 200 to 600 | 444 | 112 |
| Water | 30 to 250 | 100 | 0 |
| Sodium | 600 to 1200 | 892 | 98 |
| Potassium | 500 to 1000 | 774 | 62 |
| R11 | -40 to 120 | 24 | -111 |
Next, I developed a segmented thermal resistance model to accurately capture the dynamic heat transfer processes in the electric vehicle battery system. Traditional integrated thermal resistance models often overlook the distinct phase-change phenomena in the evaporator and condenser sections, leading to significant errors. In contrast, the segmented model divides the heat pipe into evaporator and condenser parts, with the condenser further split into plain tube and finned tube sections. The thermal resistances for the evaporator section ($R_e$) and condenser sections ($R_{c1}$ and $R_{c2}$) are defined as follows:
$$ R_e = R_{e,\text{wall}} + R_{e,\text{wick}} + R_{e,\text{eva}} $$
$$ K_e = \frac{L_e}{R_e A_e} $$
$$ R_{c1} = R_{c,\text{con1}} + R_{c,\text{wick1}} + R_{c,\text{wall}} $$
$$ K_{c1} = \frac{L_{c1}}{R_{c1} A_{c1}} $$
$$ R_{c2} = R_{c,\text{con2}} + R_{c,\text{wick2}} + R_{c,\text{tin}} $$
$$ K_{c2} = \frac{L_{c2}}{R_{c2} A_{c2}} $$
Here, $K_e$, $K_{c1}$, and $K_{c2}$ represent the heat transfer coefficients for the respective sections, with $L$ denoting length and $A$ the cross-sectional area. This model was coupled with a battery thermal model using a tetrahedral mesh with over 3.4 million elements, enabling precise simulation of temperature distributions. The coupling accounted for boundary conditions where batteries were cooled by heat pipes or air, focusing on the y-axis due to its highest temperature gradient. This approach is vital for electric vehicle applications, as it ensures accurate predictions of thermal behavior in China EV batteries under real-world conditions.
To evaluate the cooling performance of the flat ultra-thin micro heat pipe, I conducted simulations under constant current discharge rates of 1C to 3C, with initial battery temperatures matching the ambient environment. The results compared the segmented and integrated thermal resistance models. For the segmented model, the maximum battery pack temperature was 31.2°C, with a maximum temperature difference of 6.8°C. In contrast, the integrated model showed a higher maximum temperature of 35.7°C and a larger temperature difference of 8.9°C. This demonstrates the superior accuracy of the segmented model in predicting dynamic temperature changes, which is crucial for preventing thermal runaway in electric vehicle power batteries. The temperature distribution was most uneven in the central region near the positive terminal, with individual cell temperature differences reaching up to 5.2°C for the segmented model and 7.5°C for the integrated model. These findings underscore the importance of precise thermal modeling for the safety and efficiency of electric vehicles, especially in the rapidly growing China EV market.
Further analysis involved testing the heat pipe under different convection conditions: natural convection without heat pipes, forced convection without heat pipes, natural convection with flat ultra-thin micro heat pipes, and forced convection with flat ultra-thin micro heat pipes. The results, summarized in Table 2, highlight the enhanced cooling performance when heat pipes are integrated. For instance, under forced convection with heat pipes at a 3C discharge rate, the maximum battery pack temperature was only 21.3°C, with a maximum temperature difference of 4.3°C and an individual cell difference of 3.5°C. In comparison, natural convection without heat pipes resulted in temperatures up to 39.6°C and differences of 8.6°C. This clearly shows that the flat ultra-thin micro heat pipe significantly reduces heat accumulation, making it suitable for both small and large electric vehicle power battery systems in China EV applications.
| Cooling Method | Discharge Rate (C) | Max Battery Pack Temperature (°C) | Max Battery Pack Temperature Difference (°C) | Max Individual Cell Temperature Difference (°C) |
|---|---|---|---|---|
| Natural convection without heat pipe | 1 | 26.5 | 6.3 | 4.5 |
| Natural convection without heat pipe | 2 | 31.6 | 7.8 | 4.7 |
| Natural convection without heat pipe | 3 | 39.6 | 8.6 | 5.9 |
| Forced convection without heat pipe | 1 | 23.6 | 5.78 | 4.3 |
| Forced convection without heat pipe | 2 | 26.8 | 7.1 | 4.4 |
| Forced convection without heat pipe | 3 | 33.6 | 8.2 | 5.6 |
| Natural convection with flat ultra-thin micro heat pipe | 1 | 21.9 | 5.6 | 4.2 |
| Natural convection with flat ultra-thin micro heat pipe | 2 | 24.9 | 6.7 | 4.4 |
| Natural convection with flat ultra-thin micro heat pipe | 3 | 30.6 | 7.8 | 5.3 |
| Forced convection with flat ultra-thin micro heat pipe | 1 | 13.2 | 3.4 | 2.7 |
| Forced convection with flat ultra-thin micro heat pipe | 2 | 17.2 | 4.0 | 3.1 |
| Forced convection with flat ultra-thin micro heat pipe | 3 | 21.3 | 4.3 | 3.5 |
In addition to cooling, I investigated the heating performance of the flat ultra-thin micro heat pipe in low-temperature environments, which is critical for electric vehicle operation in cold climates. Two heating methods were compared: direct battery heating and heat pipe heating, with heat sources set at 180 W and initial ambient temperatures of 0°C, -10°C, and -20°C. For direct battery heating, the heating rate was initially faster, taking approximately 163 seconds to raise the surface center temperature of cell 1 to 20°C at 0°C ambient, compared to 300 seconds for heat pipe heating. However, the heat pipe method provided more uniform temperature distribution, with an average heating power ratio of 1.32 times that of direct heating. This efficiency is due to the heat pipe’s ability to distribute heat evenly across the battery pack, reducing the risk of localized hotspots. The temperature rise in the evaporator and condenser sections followed a linear trend, with the evaporator reaching 20°C in about 260 seconds at -10°C ambient, while the condenser temperature was around 9°C initially and increased gradually. These results validate the flat ultra-thin micro heat pipe’s capability for effective heating in electric vehicle power batteries, supporting the broader adoption of China EV technologies in diverse environmental conditions.
The mathematical modeling of the heating process can be described using the energy balance equations. For the evaporator section, the heat transfer rate ($Q_e$) is given by:
$$ Q_e = K_e A_e (T_{\text{cell}} – T_e) $$
where $T_{\text{cell}}$ is the battery cell temperature and $T_e$ is the evaporator temperature. Similarly, for the condenser sections, the heat dissipation rates are:
$$ Q_{c1} = K_{c1} A_{c1} (T_{c1} – T_{\text{air}}) $$
$$ Q_{c2} = K_{c2} A_{c2} (T_{c2} – T_{\text{air}}) $$
where $T_{\text{air}}$ is the ambient air temperature. These equations help in optimizing the heat pipe design for maximum efficiency in electric vehicle applications. Moreover, the transient temperature response during heating can be modeled using the lumped capacitance method for simplicity, though the full segmented model provides more accuracy. For instance, the time constant ($\tau$) for heating can be approximated as:
$$ \tau = \frac{\rho V c_p}{h A} $$
where $\rho$ is density, $V$ is volume, $c_p$ is specific heat, $h$ is the heat transfer coefficient, and $A$ is the surface area. This approach allows for quick estimations in the design phase of electric vehicle battery systems.
Throughout this research, I have emphasized the importance of thermal management for electric vehicle power batteries, particularly in the context of China’s evolving EV market. The flat ultra-thin micro heat pipe not only addresses cooling needs but also provides efficient heating solutions, ensuring battery reliability across a wide temperature range. The segmented thermal resistance model coupled with the battery thermal model has proven to be a robust tool for predicting temperature dynamics, with simulations showing minimal deviations from experimental data. For example, the maximum temperature error between the segmented model and actual measurements was less than 2°C in most cases, whereas the integrated model exhibited errors up to 4°C. This precision is essential for developing next-generation thermal management systems that can handle the high demands of electric vehicles, including fast charging and high discharge rates.
In conclusion, my study demonstrates that the flat ultra-thin micro heat pipe is a highly effective solution for thermal management in electric vehicle power batteries, especially in low-temperature environments. The segmented thermal resistance model offers significant improvements over traditional approaches, enabling accurate predictions of temperature fields and enhancing battery safety. As the electric vehicle industry, particularly in China, continues to grow, integrating such advanced thermal management technologies will be crucial for achieving long battery life, optimal performance, and reduced environmental impact. Future work could focus on optimizing the heat pipe geometry for specific electric vehicle models and exploring hybrid systems combining heat pipes with other cooling methods like liquid cooling or phase-change materials. This research contributes to the ongoing efforts to make electric vehicles more reliable and efficient, supporting the global transition to sustainable transportation.