The global push for decarbonization, driven by regulatory policies and environmental needs, is accelerating the transition from internal combustion engine vehicles to clean energy alternatives, with electric vehicles (EVs) emerging as a primary solution. At the heart of this transformation lies the lithium-ion battery (LIB), which has become the dominant energy storage technology for modern EVs due to its high energy density (250–300 Wh·kg-1), low self-discharge rate (<3% per month), and long cycle life (>2000 cycles). However, LIBs present significant thermal challenges. Their electrochemical systems require precise temperature control within the range of 20–40 °C to prevent issues such as capacity fade (>15% at 45 °C), solid electrolyte interphase layer degradation, and thermal runaway risk. Effective thermal management is thus critical for maintaining peak temperatures below 40 °C and ensuring temperature differences between cells remain under 5 °C. These operational limits highlight the necessity for advanced Battery Thermal Management Systems (BTMS) capable of maintaining optimal thermal conditions under various operating scenarios.
An efficient BTMS not only extends battery lifespan but also enhances the overall energy efficiency of the system. Currently, primary technologies employed in BTMS include air cooling, liquid cooling, phase change materials (PCM), and thermoelectric cooling (TEC). In recent years, air and liquid cooling have been widely applied and successfully commercialized. The application of PCMs is often limited by their low intrinsic thermal conductivity. Thermoelectric cooling, with its advantages of precise temperature control and rapid response, has emerged as a promising thermal management technology. Based on these different cooling techniques, various BTMS prototypes have been developed and implemented in practical EVs.
The geometric configuration of a lithium-ion battery fundamentally influences the thermal performance of its BTMS. These batteries can be manufactured in various shapes, including cylindrical, pouch, and prismatic formats. Among these, prismatic batteries are extensively used in the EV industry due to their structural simplicity, high packaging reliability, and production yield. However, the relatively large thickness of prismatic cells can hinder internal heat dissipation during operation, potentially leading to excessive temperature gradients and an increased risk of thermal runaway. Consequently, research on prismatic battery thermal management emphasizes the adoption of high-performance heat dissipation devices and corresponding optimization to meet stringent cooling requirements. For instance, some studies have proposed liquid-cooled BTMS with comprehensively optimized channel designs, hybrid BTMS combining PCM with air cooling, and space-intensive BTMS with parallel microchannels. To address the more rigorous heat dissipation demands of prismatic batteries, researchers have proposed numerous practical BTMS configurations building upon traditional structures and conducted corresponding performance optimizations.
However, conventional air cooling suffers from drawbacks such as significant fan noise and large volume, while liquid cooling faces potential leakage issues and high system complexity. Thermoelectric coolers, as an emerging cooling technology, offer distinct advantages for prismatic battery thermal management, including quiet operation, compact design, precise temperature control, and rapid response. During operation, a TEC absorbs heat at its cold side via the Peltier effect but simultaneously accumulates heat at its hot side. An increasing temperature difference between these two sides can degrade the TEC’s cooling performance. Therefore, TECs are often integrated with other cooling methods to form hybrid BTMS for effective overall battery temperature regulation. Specifically, combining TECs with air or liquid cooling can eliminate the need for complex air or coolant channels, thereby reducing system complexity. Prior research has demonstrated that hybrid systems integrating TECs with vapor chambers (VC) and liquid cooling can achieve superior thermal performance. Nevertheless, configurations involving folded VCs can be difficult to manufacture and are structurally complex, with limited analysis on their thermal performance for large prismatic batteries.
To ensure favorable thermal performance for prismatic batteries, this study proposes a novel BTMS design based on a traditional liquid-cooled system. This design employs VCs of reduced area to transfer battery heat to TECs, with simple air-cooled heat sinks dissipating heat from the TEC hot sides. A three-dimensional thermal-electric-fluid multiphysics model is developed to predict the thermal performance of the proposed BTMS. Utilizing this model, the coupled effects of coolant mass flow rate, air-side convection coefficient, and TEC input current on the system’s thermal behavior are thoroughly analyzed. The findings provide valuable insights for the thermal management of prismatic batteries.
1. Architecture of the Proposed Battery Thermal Management System
The proposed BTMS comprises prismatic lithium-ion batteries, vapor chambers (VCs), liquid cold plates (LCPs), thermoelectric coolers (TECs), and air-cooled heat sinks. The overall structure follows a layered arrangement: prismatic battery, VC, prismatic battery, LCP, prismatic battery, VC, and so on. On the battery sides, heat transferred through the VCs is dissipated by the TECs and their attached air-cooled heat sinks. To reduce computational workload, a basic unit containing two prismatic batteries is adopted as the research object, as shown in the system schematic. Each prismatic battery has a capacity of 50 Ah and dimensions of 186 × 136 × 30 mm3. The VCs, with dimensions of 230 × 136 × 3 mm3, are simplified as solid blocks with an ultra-high effective thermal conductivity of 4000 W·m-1·K-1 for numerical simulation. Two TECs are symmetrically installed on the edges of each VC. Each TEC consists of 127 p/n thermocouple pairs, 256 copper electrodes, and two ceramic plates. When current is applied to a TEC, its cold side absorbs heat from the VC via the Peltier effect, while its hot side rejects heat through an air-cooled heat sink (dimensions: 136 × 40 × 36.2 mm3, fin thickness/spacing: 1 mm). A 2 mm gap is maintained between the TECs and the battery to avoid direct thermal contact. Considering the more significant heat accumulation in prismatic cells compared to other configurations, LCPs are also placed between every two batteries, alternating with the VCs. Since a basic unit of two batteries is studied, LCPs are shown at the top and bottom of the cell pair. Each LCP has dimensions of 186 × 136 × 10 mm3 and features a U-shaped cooling channel with an 8 mm diameter to ensure sufficient cooling capacity. The VCs, TECs, and heat sinks form an integrated system to cool the sides of the prismatic cells, while the LCPs cool the opposite sides, ensuring uniform heat dissipation from the batteries. The LCPs and heat sinks are made of aluminum. Material properties for the VCs and batteries are referenced from prior studies, as summarized in Table 1.
| Property | Aluminum | Vapor Chamber | Battery |
|---|---|---|---|
| Density (kg·m-3) | 2700 | 8978 | 1838.2 |
| Specific Heat Capacity (J·kg-1·K-1) | 900 | 381 | 1150 |
| Thermal Conductivity (W·m-1·K-1) | 237 | 4000 | kx=15.3, ky=15.3, kz=0.9 |
Given the high cost of nanostructured thermoelectric materials, commercially available Bismuth Telluride-based TECs are used in this study. Each TEC has overall dimensions of 40 × 40 × 3.4 mm3. Table 2 provides detailed dimensions and temperature-dependent material parameters for its components.
| Component | Seebeck Coefficient (µV·K-1) | Electrical Resistivity (Ω·m) | Thermal Conductivity (W·m-1·K-1) | Dimensions (L×W×H mm3) |
|---|---|---|---|---|
| P-type leg | $-1.593 \times 10^{-9}T^2 + 1.364 \times 10^{-6}T – 7.062 \times 10^{-5}$ | $1.311T^2 – 1.364 \times 10^{3}T + 4.023 \times 10^{5}$ | $1.071 \times 10^{-5}T^2 – 8.295 \times 10^{-3}T + 2.625$ | 1.4 × 1.4 × 1.6 |
| N-type leg | $7.393 \times 10^{-11}T^2 – 2.500 \times 10^{-7}T – 8.494 \times 10^{-5}$ | $0.657T^2 – 7.136 \times 10^{2}T + 2.463 \times 10^{5}$ | $1.870 \times 10^{-5}T^2 – 1.447 \times 10^{-2}T + 3.680$ | 1.4 × 1.4 × 1.6 |
| Copper Electrode | – | $5.998 \times 10^{-7}$ | 400 | 3.8 × 1.4 × 0.2 |
| Ceramic Plate | – | – | 22 | 40 × 40 × 0.7 |
2. Development of the Multiphysics Numerical Model
2.1. Governing Equations for the Thermal-Electric-Fluid Coupled Model
Different computational domains within the BTMS are governed by distinct sets of equations. These can be categorized into three parts: solid domains without electric current, the thermoelectric cooler domain, and the fluid domain.
2.1.1. Governing Equations for Solid Domains
The prismatic battery cells obey the energy conservation law:
$$ \nabla \cdot (k_b \nabla T_b) + Q = 0 $$
where the subscript $b$ denotes the battery, $T$ is temperature, $k$ is thermal conductivity, and $Q$ is the volumetric heat generation rate, calculated as:
$$ Q = \frac{Q_b}{V_b} $$
Here, $Q_b = 29.9 \text{ W}$ represents the total heat generation power of a single battery at a 2C discharge rate, and $V_b$ is the cell volume.
The energy conservation equation for the aluminum LCPs and heat sinks is:
$$ \nabla \cdot (k_{al} \nabla T_{al}) = 0 $$
where the subscript $al$ denotes aluminum.
2.1.2. Governing Equations for the Thermoelectric Cooler Domain
All components within the TEC must comply with the energy conservation law:
$$ \nabla \cdot (k_m \nabla T_m) + \dot{S}_m = 0 $$
Here, $m$ denotes different material names. $\dot{S}_m$ is the energy source term representing parasitic heat generated by thermoelectric effects, including Joule heating, Thomson heat, and Peltier heat. The source terms for different components are:
$$
\dot{S}_m =
\begin{cases}
\sigma_p^{-1} J^2 – \nabla \alpha_p(T) J T_p – \frac{\partial \alpha_p(T)}{\partial T_p} T_p J \cdot \nabla T, & \text{for p-type leg} \\
\sigma_n^{-1} J^2 – \nabla \alpha_n(T) J T_n – \frac{\partial \alpha_n(T)}{\partial T_n} T_n J \cdot \nabla T, & \text{for n-type leg} \\
\sigma_{co}^{-1} J^2, & \text{for copper electrode} \\
0, & \text{for VC, heat sink, LCP, ceramic plate}
\end{cases}
$$
where subscripts $p$, $n$, $co$, and $ce$ denote p-type leg, n-type leg, copper electrode, and ceramic plate, respectively. $\sigma^{-1}$, $J$, and $\alpha$ are electrical resistivity, current density vector, and Seebeck coefficient, respectively.
Furthermore, components involving electric current—namely the p/n legs and copper electrodes—also obey charge conservation and current continuity principles:
$$ \vec{E} = -\nabla \phi + \alpha_{p,n}(T) \nabla T $$
$$ J = \sigma_m \vec{E} $$
$$ \nabla \cdot J = 0 $$
where $\phi$ and $\vec{E}$ are electric potential and electric field density vector, respectively.
2.1.3. Governing Equations for the Fluid Domain
In this work, the mass flow rate in the coolant channels is less than 4 g/s. Combined with an 8 mm diameter, the calculated Reynolds number is below 2000; therefore, the flow is considered laminar. The fluid flow follows the conservation laws of mass, energy, and momentum:
$$ \nabla \cdot \vec{v} = 0 $$
$$ \nabla \cdot (\rho_w c_w \vec{v} T_w) – \nabla \cdot (k_w \nabla T_w) = 0 $$
$$ \nabla \cdot (\rho \vec{v} \vec{v}) = -\nabla p + \nabla \cdot (\mu \nabla \vec{v}) $$
where the subscript $w$ denotes water. $\rho$, $c$, $\vec{v}$, $p$, and $\mu$ represent density, specific heat capacity at constant pressure, velocity vector, pressure, and dynamic viscosity, respectively.
2.2. Boundary Conditions and Finite Element Model Setup
The finite element method is employed to solve the above equations using the COMSOL Multiphysics software. Necessary boundary conditions are defined for the simulation. For the electric field, a current input boundary condition is applied to the positive terminal of each TEC, with the negative terminal grounded. To investigate the influence of TEC input parameters on the BTMS thermal performance, the input current is varied from 0.3 A to 1.0 A in increments of 0.1 A.
For the fluid field, a mass flow inlet boundary condition and a pressure outlet boundary condition are applied to the coolant channel’s inlet and outlet surfaces, respectively. The inlet water temperature is set to 20 °C. The water mass flow rate ($\dot{m}_w$) is varied from 1.0 g/s to 4.0 g/s in increments of 0.5 g/s to analyze its effect. The outlet pressure is defined as standard atmospheric pressure.
For the thermal field, the heat source boundary condition is defined within the battery volume, as per Eq. (2).
A convective heat transfer boundary condition is applied to the surfaces of the air-cooled heat sinks:
$$ -k \frac{\partial T}{\partial n} = h_{air} (T_{air} – T) $$
where $h_{air}$ is the air-side heat transfer coefficient, and $T_{air} = 20 °C$ is the ambient temperature. $h_{air}$ is varied from 10 to 45 W·m-1·K-1 to analyze the impact of air cooling on the BTMS performance.
Mesh independence is crucial for ensuring simulation accuracy. Four mesh densities with 997,936, 1,254,724, 1,630,848, and 2,044,222 elements were tested under the boundary conditions of TEC current = 0.8 A, $\dot{m}_w$ = 3.5 g/s, and $h_{air}$ = 25 W·m-1·K-1. The results, shown in Table 3, indicate that the battery’s maximum temperature and surface temperature difference stabilize when the element count exceeds 1,630,848. Therefore, this mesh density is selected for all subsequent simulations to balance accuracy and computational efficiency. The corresponding finite element model mesh is shown in the grid distribution figure.
| Mesh Density (Elements) | Maximum Temperature (°C) | Temperature Difference (°C) |
|---|---|---|
| 997,936 | 28.29 | 5.07 |
| 1,254,724 | 28.26 | 5.02 |
| 1,630,848 | 27.56 | 4.99 |
| 2,044,222 | 27.51 | 4.98 |
2.3. Power Consumption of the Liquid Cooling Subsystem
The liquid cooling subsystem suppresses heat accumulation on the side of the prismatic battery opposite the VC, helping to maintain cooling uniformity. The associated pump power consumption is determined by:
$$ P_{pump} = \frac{\dot{m}_w (P_{in} – P_{out})}{\rho_w} $$
where $\dot{m}_w$ is the coolant mass flow rate, $\rho_w$ is the coolant density, and $P_{in}$ and $P_{out}$ are the inlet and outlet pressures, respectively. For the given configuration, the liquid cooling subsystem power consumption is calculated to be 2.5 W.
2.4. Model Validation
The proposed BTMS prototype is currently under fabrication. Therefore, experimental data from a previously published work involving a similar hybrid VC-TEC system is used for model validation. The key difference lies in the structural configuration (folded VC in the prior work vs. the flat VC design here). The comparison between numerical and experimental results for maximum temperature difference under different cooling modes (VC only, TEC only, VC&TEC hybrid) shows a maximum deviation of approximately 5.3% for the VC-only case and a minimum deviation of about 3% for the hybrid VC&TEC case. This agreement supports the validity of the present numerical model for subsequent analysis.
3. Results and Discussion
This section comprehensively investigates the influence of key cooling parameters—air-side heat transfer coefficient ($h_{air}$), coolant mass flow rate ($\dot{m}_w$), and TEC input current ($I_{TEC}$)—on the thermal performance of the developed BTMS. Their coupled relationships are crucial for guiding practical application.
3.1. Investigation of the Operational Range for TEC Input Current
The thermal-electric-fluid multiphysics model is used to simulate the BTMS thermal performance under different TEC input currents, with $h_{air}$ and $\dot{m}_w$ fixed at 25 W·m-1·K-1 and 3.5 g/s, respectively. Increasing $I_{TEC}$ generally improves cooling performance. Specifically, as $I_{TEC}$ increases slightly from 0.3 A to 0.7 A, the maximum battery temperature decreases from approximately 27 °C to about 25 °C. However, further increasing $I_{TEC}$ yields diminishing returns in temperature reduction while significantly increasing the heat load on the air-cooled heat sink and the TEC’s own power consumption. Therefore, a rational input current is needed to ensure thermal performance while maintaining low power consumption.
Furthermore, excessive $I_{TEC}$ can amplify the temperature difference across the battery due to overcooling near the VC interface. The detailed temperature distribution on the prismatic battery surfaces under different $I_{TEC}$ values reveals that when $I_{TEC}$ exceeds 0.9 A, the battery surface in contact with the VC becomes overcooled. Currents between 0.5 A and 0.8 A appear to provide the best balance of thermal performance. Although operating at 0.8 A results in a marginally higher temperature difference (increase of ~0.2 °C) compared to 0.7 A, it better balances cooling performance and energy efficiency, making it a preferable operating point. The analysis identifies two distinct sub-optimal regimes at the extremes. At the lower limit of 0.3 A, the system exhibits insufficient cooling, leading to a high maximum temperature of 26.83 °C and an excessive temperature difference of 5.2 °C. At the upper limit of 1.0 A, while the maximum temperature drops to 25.14 °C, the temperature difference is 4.56 °C, and local overcooling occurs at the VC interface. This nonlinear response underscores the need for precise current regulation in the BTMS operation.
3.2. Coupled Effect of Air Convection Coefficient and Coolant Mass Flow Rate
With $I_{TEC}$ fixed at the optimal 0.8 A, the BTMS thermal performance is analyzed for different $h_{air}$ values. Figure 6(a) shows how coolant mass flow rate affects the maximum battery surface temperature at constant $h_{air}$. At a fixed $\dot{m}_w$, the maximum temperature decreases as $h_{air}$ increases. Notably, the reduction is significant when $h_{air}$ increases from 10 to 30 W·m-1·K-1, after which the temperature curve flattens. Conversely, at a fixed $h_{air}$, increasing $\dot{m}_w$ also lowers the maximum temperature, with substantial reductions observed in the lower range (1.0 to 2.5 g/s) and stabilization between 3.0 and 4.0 g/s.
Figure 6(b) illustrates the effect of $\dot{m}_w$ on the maximum temperature difference across the battery surface for different $h_{air}$ values. For various $h_{air}$, the temperature difference first decreases and then slightly increases with $\dot{m}_w$, reaching a minimum of 4.06 °C at $\dot{m}_w$ = 3.5 g/s. At a constant $\dot{m}_w$, as $h_{air}$ increases slightly from 10 to 25 W·m-1·K-1, the temperature difference drops from about 5 °C to near 4.1 °C. However, a further increase in $h_{air}$ leads to a slight increase and subsequent leveling off of the temperature difference, accompanied by increased fan power consumption for the heat sink. Therefore, the minimum temperature difference is achieved when $h_{air}$ = 25 W·m-1·K-1 and $\dot{m}_w$ = 3.5 g/s.
3.3. Coupled Effect of Coolant Mass Flow Rate and TEC Input Current
This section investigates the influence of $I_{TEC}$ on BTMS thermal performance under different $\dot{m}_w$, with $h_{air}$ fixed at 25 W·m-1·K-1. Figure 7(a) clearly shows that the maximum battery temperature decreases linearly with increasing $\dot{m}_w$; however, this reduction becomes less pronounced once $\dot{m}_w$ exceeds 3.0 g/s. At the upper limit of 3.5 g/s, the maximum temperature is controlled below 27 °C. Figure 7(b) indicates that for $\dot{m}_w$ conditions above 1.0 g/s, the minimum temperature difference consistently occurs at $I_{TEC}$ = 0.8 A. When $\dot{m}_w$ = 3.5 g/s, the maximum temperature difference can be controlled to 4.06 °C, representing the system’s optimal operating point regarding flow rate.
3.4. Coupled Effect of Air Convection Coefficient and TEC Input Current
At the optimal coolant mass flow rate of 3.5 g/s, the effect of $I_{TEC}$ on BTMS thermal performance is further analyzed for different $h_{air}$ values. Figure 8(a) shows that for different $h_{air}$ curves, the maximum battery temperature decreases as $I_{TEC}$ increases. The reduction becomes less noticeable when $h_{air}$ exceeds 30 W·m-1·K-1. From Figure 8(b), it can be observed that for $h_{air}$ values between 25 and 45 W·m-1·K-1, the maximum temperature difference first decreases and then increases with increasing current. This is because enhanced air cooling performance improves the TEC’s heat dissipation efficiency, potentially leading to overcooling on the battery side adjacent to the VC. Since the coolant mass flow rate remains constant, an excessive temperature difference can develop between the two ends of the prismatic cell, posing a potential safety risk. For $h_{air}$ = 25 W·m-1·K-1, the temperature difference at 0.7 A is noticeably higher than at 0.8 A. Conversely, for $h_{air}$ between 35–45 W·m-1·K-1, the temperature difference at 0.7 A is slightly lower than at 0.8 A, an effect particularly pronounced at $h_{air}$ = 45 W·m-1·K-1. However, this condition results in excessively high system energy consumption and waste. Therefore, maintaining $h_{air}$ at 25 W·m-1·K-1 optimally balances temperature uniformity and energy efficiency.
4. Conclusion
This study proposes a novel Battery Thermal Management System (BTMS) based on vapor chambers (VCs) and thermoelectric coolers (TECs) to effectively control the temperature uniformity of prismatic lithium-ion batteries. A coupled thermal-electric-fluid multiphysics numerical model is developed to comprehensively evaluate the system’s thermal performance. The integrated effects of three key cooling parameters—air-side heat transfer coefficient ($h_{air}$), coolant mass flow rate ($\dot{m}_w$), and TEC input current ($I_{TEC}$)—on the system’s thermal behavior are thoroughly investigated. The main conclusions are as follows:
(1) The established multiphysics numerical model provides an effective method for characterizing the comprehensive temperature distribution within the BTMS. Numerical simulations demonstrate that integrating TECs with complementary cooling technologies can effectively control the battery temperature difference below the 5 °C threshold. A liquid cooling subsystem power consumption parameter of 2.5 W verifies the system as a high-efficiency thermal management solution. However, the TEC’s cooling capability exhibits a nonlinear dependence on the applied current and the temperature gradient across it. Specifically, the system shows a unique optimum point where increasing input current initially reduces the battery temperature difference until a minimum is reached. Beyond this point, further current increase exacerbates thermal gradients due to decreasing thermoelectric conversion efficiency.
(2) The BTMS integrating TECs significantly improves thermal performance and temperature uniformity. Compared to a traditional non-TEC configuration, the maximum battery temperature is reduced by 0.76 °C, and the temperature difference is lowered by 1.14 °C. To optimize the trade-off between thermal regulation efficacy and energy consumption, a comprehensive analysis of the interaction among convection coefficient, coolant flow rate, and TEC current regulation is essential.
(3) The maximum battery temperature and temperature difference vary with changes in the three cooling parameters. The results indicate that the BTMS achieves optimal thermal performance and temperature uniformity when $h_{air}$ = 25 W·m-1·K-1, $\dot{m}_w$ = 3.5 g/s, and $I_{TEC}$ = 0.8 A. Under these conditions, the maximum temperature of the prismatic battery is 25.57 °C, with a temperature difference of 4.06 °C.
(4) Developing optimized control strategies that simultaneously regulate TEC input current, liquid cooling parameters, and air-side convection conditions is crucial for achieving superior thermal management performance in the BTMS while maintaining energy efficiency. However, the inherent multi-parameter coupling and nonlinear system response associated with these interacting variables present a significant research challenge that warrants focused investigation in future work.