In the context of global energy transition, energy storage technology has become a critical solution to address the volatility and intermittency of renewable energy sources. Large-capacity energy storage cells, with their high energy density, are emerging as a key direction for new energy storage systems and electric vehicles. However, the safety of these energy storage cells cannot be overlooked, as heat generation during charge-discharge cycles leads to temperature rise, performance degradation, and even thermal runaway. This study investigates the heat generation behavior and capacity fading mechanisms of large-capacity energy storage cells under various operating conditions, employing experimental methods to analyze the relationship between thermal behavior and performance decay. The findings aim to provide guidance for the thermal management and safety design of energy storage systems.
Energy storage cells are pivotal in modern energy systems, enabling the integration of renewable sources like solar and wind. The shift toward large-capacity designs, such as those used in grid-scale storage, demands a thorough understanding of their thermal characteristics. Heat in energy storage cells arises from reversible and irreversible processes. Reversible heat is associated with electrochemical reactions, while irreversible heat includes ohmic Joule heat from internal resistance and polarization heat from electrode interfaces. The balance between these components depends on factors like state of charge (SOC), discharge rate, and ambient temperature. For instance, at low SOC, the entropy coefficient may turn negative, indicating exothermic reactions that exacerbate heat accumulation. This study delves into these aspects through systematic experiments on a 280 Ah lithium iron phosphate (LFP) energy storage cell, commonly used in stationary storage applications.
The experimental setup involved a controlled environment using a battery testing system and a climate chamber to maintain precise temperatures. The energy storage cell was subjected to various discharge rates (0.25C, 0.5C, and 1.0C) and ambient temperatures (ranging from -15°C to 45°C). Temperature was monitored at multiple points on the cell surface to capture spatial variations, and heat flux was measured to quantify thermal output. Internal resistance was evaluated using the Hybrid Pulse Power Characterization (HPPC) method, which applies short discharge and charge pulses to determine ohmic and polarization resistances. The entropy coefficient was derived from open-circuit voltage measurements at different temperatures and SOC levels. This comprehensive approach allows for a detailed analysis of how operational conditions influence the heat generation and longevity of energy storage cells.
Our results highlight the significant impact of discharge rate on heat generation. At a 1.0C discharge rate, the maximum temperature rise reached 21.64°C, compared to only 3.5°C at 0.25C. This underscores the importance of managing high-rate operations in energy storage cells to prevent overheating. The heat flux data further revealed that peak values increased with discharge rate, reaching up to 600 W/m² at 1.0C, indicating higher heat generation rates. Spatially, temperature distribution was non-uniform, with the negative terminal area exhibiting the highest温升 due to concentrated electrochemical activity. This heterogeneity emphasizes the need for targeted thermal management in large-capacity energy storage cells to mitigate hot spots and ensure uniform cooling.
The internal resistance of the energy storage cell varied with SOC and discharge rate. At mid-SOC levels (10%-90%), the total resistance remained around 0.5 mΩ, but it increased at low and high SOC due to polarization effects. The resistance components can be expressed as:
$$ R_{\Omega} = \frac{\Delta V_1}{I} $$
where \( R_{\Omega} \) is the ohmic resistance, \( \Delta V_1 \) is the instantaneous voltage drop, and \( I \) is the current. The polarization resistance \( R_{pol} \) is given by:
$$ R_{pol} = \frac{\Delta V_2 – \Delta V_1}{I} $$
with \( \Delta V_2 \) being the voltage change at the pulse end. The total resistance \( R \) is the sum:
$$ R = R_{\Omega} + R_{pol} $$
These equations help quantify the heat sources in energy storage cells, as ohmic resistance dominates Joule heating, while polarization resistance contributes to additional heat during intense cycling.
Temperature also played a crucial role in the performance of energy storage cells. At lower ambient temperatures, the heat generation increased due to higher internal resistance from reduced ion mobility in the electrolyte. For example, at -15°C, the heat flux was substantially higher than at 25°C, leading to greater温升 despite the colder environment. This inverse relationship highlights the challenges in operating energy storage cells in extreme climates. The entropy coefficient, derived from \( \frac{dU}{dT} = \frac{\Delta U}{\Delta T} \), where \( U \) is voltage and \( T \) is temperature, showed positive values in mid-SOC ranges, indicating endothermic reactions that partially offset heat generation. However, at SOC extremes, the coefficient turned negative, exacerbating thermal issues. This behavior is critical for designing thermal management systems that maintain energy storage cells within optimal temperature ranges.
Capacity fading in energy storage cells was closely linked to temperature. Accelerated cycle tests at 25°C, 35°C, and 45°C revealed that higher temperatures accelerated degradation. After 100 cycles at 1.0C charge-discharge rates, the capacity loss was 4.09 Ah at 25°C, 6.96 Ah at 35°C, and 10.31 Ah at 45°C, corresponding to loss rates of 1.61%, 2.45%, and 3.64%, respectively. This indicates that the degradation rate at 45°C was 2.26 times that at 25°C. The primary mechanisms include accelerated solid electrolyte interface (SEI) growth, electrolyte decomposition, and active material loss at elevated temperatures. These findings stress the importance of temperature control in prolonging the lifespan of energy storage cells.
To further analyze the aging process, incremental capacity (dQ/dV) curves were examined. These curves showed peak shifts and reductions in height with cycling, particularly at higher temperatures. The areas under the peaks, denoted as Q1, Q2, and Q3, decreased linearly with cycle count, with Q3 (high-potential peak) degrading faster in warm conditions. This suggests that high temperatures intensify side reactions, leading to rapid capacity fade in energy storage cells. The internal resistance evolution over cycles also showed increasing polarization resistance, which correlates with performance decline. Tables 1 and 2 summarize key experimental data on temperature rise and capacity fading under different conditions.
| Discharge Rate | Max Temperature Rise (°C) | Peak Heat Flux (W/m²) | Dominant Heat Source |
|---|---|---|---|
| 0.25C | 3.5 | ~200 | Reversible heat |
| 0.5C | 10.2 | ~400 | Mixed |
| 1.0C | 21.64 | ~600 | Irreversible heat |
| Ambient Temperature (°C) | Capacity Loss (Ah) | Loss Rate (%) | Dominant Aging Mechanism |
|---|---|---|---|
| 25 | 4.09 | 1.61 | SEI growth |
| 35 | 6.96 | 2.45 | Electrolyte decomposition |
| 45 | 10.31 | 3.64 | Active material loss |
The heat generation in energy storage cells can be modeled using the overall heat balance equation. The total heat generation rate \( \dot{Q} \) is the sum of irreversible and reversible components:
$$ \dot{Q} = I^2 R + I T \frac{dU}{dT} $$
where \( I \) is current, \( R \) is internal resistance, \( T \) is absolute temperature, and \( \frac{dU}{dT} \) is the entropy coefficient. At high discharge rates, the \( I^2 R \) term dominates, leading to significant温升. For instance, at 1.0C, the current is high, resulting in substantial Joule heating. In contrast, at low rates, the reversible term may cause cooling if \( \frac{dU}{dT} \) is positive. This equation helps predict thermal behavior under various scenarios, aiding in the design of cooling systems for energy storage cells.
Spatial temperature non-uniformity in large-capacity energy storage cells poses additional challenges. Our measurements showed that the upper regions, especially near the negative terminal, had temperatures up to 5°C higher than the bottom areas. This gradient is attributed to current distribution and material properties. In practical applications, such non-uniformity can lead to localized aging and reduced overall efficiency. Therefore, thermal management strategies should incorporate distributed cooling, such as liquid cooling plates or phase change materials, to maintain homogeneity. The heat flux distribution along the cell height further confirmed this, with the top third experiencing the highest fluxes. This insight is vital for optimizing the layout and cooling of energy storage cells in battery packs.
Cycle life testing revealed that energy storage cells subjected to high temperatures exhibited not only faster capacity fade but also increased internal resistance. The DC internal resistance rose by over 20% after 100 cycles at 45°C, compared to less than 10% at 25°C. This resistance growth is primarily due to SEI thickening and electrode degradation. The relationship between cycle number and resistance can be approximated linearly for polarization resistance, emphasizing the cumulative effect of cycling. For energy storage cells used in frequent charge-discharge applications, such as grid frequency regulation, managing temperature is crucial to sustain performance and avoid premature failure.
Incremental capacity analysis provided deeper insights into the aging mechanisms. The dQ/dV curves for energy storage cells cycled at 45°C showed pronounced right shifts and peak attenuation, indicating loss of lithium inventory and active material. The peak areas Q1, Q2, and Q3 decreased steadily, with Q3 degrading fastest at high temperatures. This aligns with the theory that high potentials accelerate parasitic reactions. Mathematical modeling of these curves can help estimate remaining capacity and predict end-of-life for energy storage cells. For example, the rate of peak area reduction \( \frac{dQ}{dN} \), where \( N \) is cycle number, can be used in prognostic algorithms.
Environmental factors beyond temperature also affect energy storage cells. For instance, humidity and mechanical stress can influence sealing integrity and lead to internal short circuits. However, this study focused on thermal aspects, as heat is a primary driver of degradation in energy storage cells. Future work could explore multi-stress aging to develop more comprehensive models.
The implications of this research extend to battery management system (BMS) design. By understanding the heat generation patterns and capacity fading trends, BMS algorithms can incorporate thermal constraints to optimize charging profiles. For example, reducing charge current at high temperatures or low SOC can mitigate heat buildup. Additionally, real-time temperature monitoring at critical points, like the negative terminal, can trigger cooling mechanisms before thermal runaway occurs. These strategies are essential for safe and efficient operation of large-capacity energy storage cells in demanding applications.
In conclusion, this study demonstrates that discharge rate and ambient temperature significantly influence the heat generation and capacity fading of large-capacity energy storage cells. High rates lead to substantial温升 and non-uniform temperature distributions, while elevated temperatures accelerate degradation through various mechanisms. The experimental data and models presented here provide a foundation for improving thermal management and prolonging the life of energy storage cells. As the adoption of energy storage systems grows, these insights will be invaluable in ensuring reliability and safety. Future research should focus on advanced materials and cooling techniques to further enhance the performance of energy storage cells under diverse operating conditions.