In the rapidly evolving field of electric vehicles, the thermal safety and efficiency of lithium-ion battery packs are paramount. As a researcher focused on energy storage systems, I have dedicated significant effort to addressing the critical challenges associated with battery heat generation and dissipation. The performance and longevity of lithium-ion batteries are intimately tied to their operating temperature. Deviations from the optimal range of 20–40°C can accelerate capacity fade, while local hotspots exceeding 80°C may trigger thermal runaway, leading to catastrophic failures such as fire or explosion. Traditional thermal management solutions, including air cooling, liquid cooling, and phase change materials (PCMs), often fall short in balancing散热 efficiency and temperature uniformity under high-rate charging and discharging scenarios. For instance, air cooling systems exhibit significant thermal lag at discharge rates above 3C, while conventional liquid cooling plates, due to simplistic flow channel designs, can result in temperature differences exceeding 8°C among cells, hastening battery pack degradation. This article presents our comprehensive work on developing a hybrid liquid-cooling-PCM thermal management system, aiming to enhance both safety and performance through innovative design and rigorous evaluation. The core of this system integrates seamlessly with the overall battery management system (BMS), ensuring precise thermal regulation as part of a holistic BMS strategy.
The effectiveness of any battery management system hinges on understanding the fundamental heat generation mechanisms within lithium-ion batteries. Heat in these batteries arises primarily from irreversible energy dissipation processes, including Joule heating due to ohmic resistance, polarization heat from electrochemical reactions, and heat from side reactions. The ohmic component often constitutes over 65% of the total heat generation, and its intensity scales quadratically with current, leading to exponential increases in heat production power at high discharge rates. Our experimental data indicate that for a typical NMC (nickel-manganese-cobalt) cell, the peak heat generation power surges from 12.3 W at 1C to 98.7 W at 3C discharge. This heat is not uniformly distributed within the cell; gradients exist from the core to the surfaces, exacerbating temperature disparities. Temperature sensitivity is bidirectional: at low temperatures (below 0°C), lithium-ion mobility decreases, reducing usable capacity by 30–50% and promoting lithium dendrite growth. At elevated temperatures (above 45°C), the solid-electrolyte interphase (SEI) layer destabilizes, initiating exothermic reactions between the anode and electrolyte. If local temperatures accumulate to around 120°C, oxygen release from the cathode can trigger irreversible thermal runaway. Thus, a sophisticated battery management system must proactively manage these thermal dynamics to maintain cells within the safe operational window.
To address these challenges, we propose a multi-level协同 thermal management architecture that synergistically combines modular liquid cooling plates with graphene-enhanced phase change materials. This design is integral to the thermal regulation module of the battery management system. The liquid cooling component employs a serpentine-parallel hybrid flow channel topology. Traditional single-path serpentine channels are redesigned into three parallel sub-channels (inlet layer, core layer, outlet layer), enabling gradient distribution of coolant velocity. The matching between coolant flow rate and channel parameters is quantified using fluid dynamics equations. The relationship between coolant volumetric flow rate \(Q\), cross-sectional area \(A\), and velocity \(v\) is given by:
$$Q = \rho v A$$
where \(\rho\) is the coolant density. As the discharge rate escalates from 1C to 3C, our system dynamically adjusts the pump power via a PID algorithm, linearly increasing \(Q\) from 0.12 m³/h to 0.35 m³/h. This ensures that the cooling power keeps pace with the heat generation rate. For the PCM component, key parameters are optimized. The effect of graphene doping on thermal conductivity \(\lambda\) follows the relationship:
$$\lambda_{\text{复合}} = \lambda_{\text{PCM}} (1 + 2.7\phi)$$
where \(\phi\) is the graphene mass fraction (\(0 \leq \phi \leq 15\%\)). At \(\phi = 12\%\), the composite’s thermal conductivity reaches 6.8 W/(m·K), a 320% improvement over pure PCM, while the phase change latent heat experiences only a 9.3% reduction. This enhancement allows the PCM to absorb and redistribute heat more efficiently, acting as a thermal buffer that reduces the load on the active liquid cooling system.
A dynamic temperature control strategy, implemented within the BMS software, adopts a hierarchical architecture. The底层 sensor network配置s seven measurement points per module (two at cell tabs, three at cell centers, two at the PCM interface) to capture temperature field data. The上层 controller switches between PID and fuzzy control modes based on temperature difference thresholds. When the module’s average temperature is below 45°C, the PID algorithm maintains temperature uniformity with ±0.5°C precision. If localized temperature spikes exceed a 5°C gradient, the fuzzy rule库 is activated. It调节s coolant flow rate and PCM activation zones based on weighted values of temperature change rate and spatial gradient. In simulated NEDC (New European Driving Cycle)工况 tests, this strategy reduced the liquid cooling pump’s start-stop frequency by 64% and decreased overall system energy consumption by 21%. This intelligent control is a cornerstone of an advanced battery management system, enabling both efficiency and reliability.
To validate the engineering applicability of our hybrid system, we established a multi-scale simulation model and a full-scale experimental platform. Numerical simulations were conducted using ANSYS Fluent to build a three-dimensional coupled thermal-fluid model encompassing a battery module composed of 20 cells (dimensions: 480 mm × 210 mm × 120 mm). The model employs unstructured meshing with a minimum grid size of 0.5 mm,局部加密 at cell tabs and PCM interfaces. The governing equations include the energy conservation equation and the Realizable \(k\)-\(\epsilon\) turbulence model. The latent heat of the PCM is handled via the equivalent heat capacity method:
$$\rho C_{\text{eff}} \frac{\partial T}{\partial t} = \nabla \cdot (\lambda \nabla T) + q_{\text{gen}}$$
where
$$C_{\text{eff}} = C_p + L \frac{\partial f}{\partial T}$$
Here, \(L\) is the phase change latent heat, and \(f\) is the liquid fraction. Boundary conditions were set at an ambient temperature of 45°C, coolant inlet temperature of 25°C, and flow velocity of 0.3 m/s. Discharge工况 included both 3C constant current and 2C pulse cycling (duty cycle 5:1). The experimental platform consisted of a high-precision battery testing system (Arbin BT-5HC), a coolant circulation unit (temperature control accuracy ±0.2°C), and an infrared thermal camera (FLIR A655sc). Eighteen T-type thermocouples (accuracy ±0.5°C) were布置 on the module surface: twelve at cell tabs and centers, and six embedded at the PCM-liquid cooling plate interface. During testing, coolant flow rate was continuously adjusted from 0.12 to 0.42 m³/h via a variable-frequency pump, with data acquired at 1 Hz for temperature, voltage, and pump energy consumption.
Performance assessment focused on three core metrics: 1) Temperature uniformity, characterized by the standard deviation \(\sigma\) of module surface temperature (target \(\sigma \leq 2°C\)); 2) Maximum temperature difference \(\Delta T\) (threshold \(\Delta T < 5°C\)); and 3) Cooling energy consumption ratio \(\eta = E_{\text{cool}} / E_{\text{cell}}\), where \(E_{\text{cool}}\) is the cooling system功耗 and \(E_{\text{cell}}\) is the total thermal energy released by the battery. The following table summarizes key comparative results between the hybrid liquid-cooling-PCM system and a traditional liquid-cooling-only system under 3C constant current discharge:
| Performance Metric | Hybrid Liquid-Cooling-PCM System | Traditional Liquid-Cooling System |
|---|---|---|
| Maximum Module Temperature | 46.3°C | 52.7°C |
| Temperature Standard Deviation (\(\sigma\)) | 1.8°C | 3.1°C |
| Maximum Temperature Difference (\(\Delta T\)) | 4.2°C | 7.5°C |
| Cooling Energy Consumption Ratio (\(\eta\)) | 0.15 | 0.18 |
| Pump Average Power (Pulse Cycling) | 46 W | 58 W |
Infrared thermography revealed that the PCM absorbed approximately 37% of the heat during the initial discharge phase (0–400 s), delaying the activation of the liquid cooling system by 120 s and contributing to the reduced pump energy. In extreme condition tests (45°C ambient temperature + 3C discharge), the hybrid system demonstrated superior robustness. At 80% state of charge (SOC), the maximum temperature difference was 4.5°C with no localized hotspots, whereas the pure liquid cooling system saw temperatures at cell centers exceed 68°C after 600 s, forcing the BMS to initiate power derating. For pulse cycling conditions, the hybrid system reduced temperature fluctuation amplitude by 62% compared to the pure liquid cooling system. Furthermore, in a thermal runaway inhibition experiment simulating a localized short circuit, the PCM limited the peak temperature at the fault point to 92°C within 120 s (compared to 143°C without PCM), delaying electrolyte leakage by 210 s and providing a critical buffer for fault handling. These results underscore how an integrated thermal management approach within the battery management system can significantly enhance safety margins.
The engineering validation leads to several quantitative conclusions: The hybrid cooling system reduces散热 energy consumption by 18% and improves temperature uniformity by 42% under high-rate conditions. The buffering efficiency of the PCM against transient thermal shocks is positively correlated with the graphene doping ratio (reaching 89% at \(\phi = 12\%\)). The dynamic temperature control strategy lowers average system power consumption by 21%, with algorithm switching response times under 0.5 s. These improvements directly contribute to the overall efficacy of the battery management system in maintaining pack health and performance.
From a practical implementation perspective, cost-benefit analysis is crucial. Considering a representative 70 kWh vehicle battery pack, the initial cost of the liquid-cooling-PCM hybrid system increases by approximately $300 (2200 RMB) compared to a traditional liquid cooling system, primarily due to graphene-PCM material and the fabrication of fractal flow channel molds. However, lifecycle maintenance costs are substantially lower: 1) Coolant replacement intervals extend from 2 years to 5 years, reducing annual maintenance costs by 65%; 2) Reduced pump power consumption decreases vehicle energy consumption by 0.8 kWh per 100 km. Over a 150,000 km vehicle lifetime, this energy saving offsets 127% of the initial cost increment. More importantly, the enhanced temperature control precision extends the battery pack’s cycle life from 2000 to 2800 cycles, equivalent to a 19% increase in residual value. This economic advantage further justifies the integration of such advanced thermal management into the broader battery management system architecture. The following table outlines the cost-benefit comparison over a 10-year period:
| Cost/Benefit Category | Hybrid System | Traditional System |
|---|---|---|
| Initial Material & Manufacturing Cost | Base + $300 | Base |
| Annual Maintenance Cost | $35 | $100 |
| Energy Cost per 100 km (Cooling) | $0.12 | $0.16 |
| Projected Cycle Life (Full Cycles) | 2800 | 2000 |
| Net Present Value (10-year, 5% discount) | Higher by ~$850 | Reference |
Looking forward, research should extend along two primary dimensions: intelligence and material innovation. On one hand, developing predictive thermal management algorithms based on deep learning is essential. Leveraging historical battery data and real-time operating conditions, such algorithms can model temperature field evolution and enable feed-forward control of the cooling system, making the BMS more proactive and adaptive. This aligns with the trend towards smarter, more integrated battery management systems. On the other hand, with the advent of solid-state batteries and 800V high-voltage platforms, there is an urgent need to develop ultra-thin microchannel cooling plates (thickness below 1 mm) and explore the thermal特性 matching between phase change materials and solid electrolytes. The thermal management system must evolve in tandem with cell technology to address new heat dissipation challenges posed by higher energy densities and faster charging capabilities. Future iterations of the battery management system will likely incorporate real-time health estimation and adaptive thermal control loops based on such advanced materials and algorithms.
In conclusion, our work demonstrates that a hybrid liquid-cooling-phase change material thermal management system offers a robust, energy-efficient solution for high-density lithium-ion battery packs. By optimizing flow channel design, enhancing PCM properties with graphene, and implementing an intelligent dynamic control strategy, we achieved significant improvements in temperature uniformity and cooling efficiency while reducing overall energy consumption. This system forms a critical component of a comprehensive battery management system, directly contributing to enhanced safety, longevity, and performance of electric vehicle batteries. The integration of passive and active cooling, governed by smart algorithms, represents a significant step forward in thermal management technology. As battery technologies continue to advance, the role of the BMS in orchestrating such complex thermal, electrical, and state-management functions will only become more central, demanding continuous innovation in both hardware and software domains. The pursuit of lower功耗, higher reliability, and greater intelligence remains the guiding principle for next-generation battery management systems.