Thermal runaway is the most serious safety issue for lithium-ion batteries, and thermal runaway is often accompanied by serious consequences of fire and smoke, posing a significant threat to the lives and property safety of lithium-ion battery users. The uncontrolled detection is mainly based on the battery temperature. According to our current knowledge, the causes of thermal runaway are generally caused by mechanical abuse and abuse of electricity, which lead to a large amount of heat in a short time, limited by the thermal diffusion conditions of the lithium-ion battery. Lithium-ion battery internal accumulation, causing positive and negative active material decomposition, release of reactive oxygen species, further lead to the decomposition of the electrolyte oxidation, resulting in more heat, and ultimately lead to thermal runaway lithium-ion battery, so we lithium-ion battery safety Control is also mainly based on its temperature monitoring.
Generally in the battery pack we will part of the cell paste temperature resistance, thermocouple, real-time detection of battery temperature, in case of abnormalities can be timely cut off the power to ensure the safety of the battery.But the current lithium-ion battery temperature monitoring mainly Is the detection of the surface temperature, but due to the characteristics of lithium-ion battery structure makes its thermal conductivity in all directions are very different, such as the University of Warwick, Thomas Grandjean and other large square lithium-ion battery thermal properties of It is found that the maximum temperature difference of 20Ah LFP battery can reach 20 ℃ in the thickness direction at 10C discharge rate, which is mainly limited by the thermal conductivity inside the battery. Therefore, the traditional measurement of the battery surface temperature makes it difficult to truly react lithium ion The internal battery temperature, the gap between the two may be in the hundreds of degrees Celsius.
People have made a lot of efforts to solve the above problems. For example, in the production process of lithium-ion batteries, thermocouples, thermocouples and the like are added to the outside of the battery by certain means, but the practicality of these methods Are not very good, the first is due to the introduction of temperature measurement equipment is difficult to protect the battery seal, the battery performance will have a negative impact, followed by these temperature components require electrical connection, the safety of lithium-ion batteries have a certain impact , So these methods only stay in the laboratory stage, it is difficult to practical.Although there are also Aalto Research Center of Ajay Raghavan, etc. proposed the use of Foldable Fibers grating internal pressure and temperature testing, and to solve the sealing problem, However, these technologies are still immature, and their practicality is still relatively poor.
In order to solve the problem of monitoring the internal core temperature of Li-ion batteries, M. Parhizi, MB Ahmed and A. Jain of the University of Texas at Arlington jointly proposed a method of predicting the core temperature of the lithium-ion battery based on the thermal model of the Li-ion battery , The method can infer its core temperature with the help of the model through the temperature of the lithium-ion battery surface, which can help us better monitor the lithium-ion battery and reduce the risk of thermal runaway.
We know there are two factors that affect the core temperature of lithium-ion batteries: 1) the battery heat production rate; 2) the thermal conductivity of the battery M. Parhizi According to the thermal characteristics of cylindrical batteries, lithium-ion batteries and thermal runaway Chemical reaction kinetics, we design a tracking model of the battery's core temperature. The model can trace the battery's core temperature in real time. The experimental results show that the model is in good agreement with the actual situation.
Taking into account the conduction into and out of the battery and the internal generation, storage of heat, you can get the following heat conduction formula
Where the boundary conditions are given by the following equation, and we assume that we can obtain the temperature T0 (t) at time t (measured) at the surface of the cell (r = R).
By solving the above equation, we can see that the core temperature of the battery is composed of the temperature T1 (0, t) determined by the battery heat production rate and T2 (0, t) determined by the temperature of the battery surface, To obtain the core temperature data of the battery, we need to know the battery heat production model and the battery thermal characteristics. Heat production model We can use the Arrhenius formula to calculate, and the battery thermal characteristics parameters such as thermal conductivity, specific heat capacity and other data can be through experiments Therefore, we can use the above model to observe the core temperature of the battery.
Tcore (t) = T1 (0, t) + T2 (0, t)
In order to verify the effectiveness of the above model, M.Parhizi using a specially designed 26650 battery was tested.The next figure is in the constant heat production rate Q0, activation energy Ea changes under the circumstances, the model predicts the trend of temperature rise Compared with the experimental data, the straight line represents the model prediction result and the hollow point represents the experimental data. It can be seen from the figure that the prediction result of the model is in good agreement with the actual test result, and the maximum deviation between the two Only about 1%.
The graph below shows the comparison between the predicted temperature rise rate and the test results under the condition that the activation energy Ea is kept constant but the heat production rate Q0 is changed. The same model prediction result is in good agreement with the test results, and the maximum deviation is only 1.2%.
The above tests show that the model designed by M. Palhizi is in good agreement with the actual test results and can accurately predict the core temperature in the battery.We need to predict the core temperature during the thermal runaway of the lithium ion battery The total heat generated during thermal runaway is calculated. The following table summarizes the heat generated by various reactions within the lithium-ion battery during thermal runaway and their trigger temperatures.
The following figure shows the lithium ion battery core temperature (calculated) and the battery surface temperature curve, we can see from the figure, in the first 600s, the battery surface temperature is higher than its core temperature, mainly because the battery initial The temperature is low, so the heat conduction from the surface to the core of the battery.But as the battery temperature rises, the heat generated by the chemical reaction increases, the battery core temperature starts to rise rapidly, the maximum temperature of the battery core in the event of thermal runaway The highest surface temperature than 400 degrees Celsius.
The graph below shows the variation of core temperature and surface temperature of 18650NMC (Li (Ni0.45Mn0.45Co0.10) O2) cell during thermal runaway. As can be seen from the figure, due to the low initial heat rate, The cell's core temperature is very close to the surface temperature, but as the temperature rises to a certain temperature, the rate of heat production increases greatly as more side reactions begin to occur, so the core temperature rapidly rises above 1000 degrees Celsius The temperature of the battery surface increases.
Figure a lithium ion battery under different thermal conductivity conditions, the battery core temperature curve, from the figure we can notice that the battery thermal conductivity change of 10%, the core temperature changes of only 2%, showing that both There is no strong correlation between Figure b is the battery with different specific heat capacity of the battery core temperature curve, the battery specific heat capacity change of 10%, the battery core temperature change of 7%, with a strong correlation Sex.
The temperature at the core of the cell is several hundred degrees Celsius above the surface of the cell in the event of a thermal runaway, so temperature changes on the surface of the cell do not accurately reflect the temperature changes inside the cell. The predictive model developed by M. Parhizi , Can accurately calculate and predict its core temperature by means of the temperature of the battery surface, the thermal characteristics of the battery and the chemical reaction kinetics parameters. The method does not require the installation of devices such as thermocouples inside the battery and does not increase the system complexity. Therefore, In practice, has a very good application prospects.
