With the continuous growth of energy storage demand, especially in the fields of electric vehicles and renewable energy systems, the safety and performance research of lithium-ion batteries have received increasing attention. Thermal runaway, as a major challenge to battery safety, is a severe exothermic reaction caused by mechanical, electrical, or thermal abuse, which may lead to catastrophic consequences. Although most thermal runaway models are designed for new battery designs, the impact of battery aging on its thermal behavior and safety is crucial. This study developed an electrochemical thermal coupling model incorporating aging effects to predict the thermal behavior and thermal runaway initiation conditions of cylindrical lithium-ion batteries.
Through experimental data verification of fresh NMC batteries and aged NCA batteries, combined with statistical analysis (p<0.05), key influencing factors were identified, and the effects of internal resistance (10-40 m Ω), capacity (1-5 Ah), and current rate (1C-8C) on temperature evolution were evaluated using a full factor design. In addition, the internal resistance threshold for thermal runaway was determined through logistic regression algorithm, and the model achieved a prediction accuracy of up to 95% on the test dataset. The results indicate that the impact of aging on battery thermal stability is complex: an increase in internal resistance exacerbates heat generation, while capacity decay reduces the risk of thermal runaway by reducing energy storage. This study provides an effective framework for optimizing battery thermal management and safety prediction mechanisms, helping to develop safer and more reliable lithium-ion energy storage systems.
1 Uncontrolled heating and safety hazards
In the wave of global energy transition, lithium-ion batteries have become the core carrier for electric vehicles and renewable energy storage due to their high energy density and compact design. However, battery safety accidents occur frequently, among which “thermal runaway” is one of the most dangerous failure modes, like a hidden “time bomb”: when the battery temperature goes out of control and skyrockets, chain reactions such as anode SEI film decomposition and electrolyte combustion can cause fires or even explosions.
Traditional research has focused on the thermal runaway mechanism of new batteries, but has overlooked a key variable – battery aging. As the usage time increases, aging phenomena such as reduced lithium inventory, loss of active materials, and increased internal resistance will occur inside the battery. How do these changes reshape the thermal safety boundary of the battery? A research team from the University of Rome in Italy has systematically revealed for the first time the complex relationship between aging and thermal runaway by constructing an electrochemical thermal coupling model, providing a new perspective for solving this safety problem.
2 Battery life and thermal safety mechanism
(1) The dual face of aging: cyclic aging vs. idle aging
Cyclic aging: In frequent charging and discharging of electric vehicles, temperature, current rate (C-rate), and depth of discharge (DOD) act like a “whetstone”, accelerating the structural degradation of electrode materials and causing the SEI film to continuously thicken, resulting in an increase in internal resistance.
Setting aside aging: Even if stored in a static state, the ambient temperature and state of charge (SOC) can quietly erode the health of the battery, leading to electrolyte decomposition at high temperatures and lithium metal deposition at low temperatures, gradually reducing the thermal stability of the battery.
(2) The “fuse” of thermal runaway: the butterfly effect of internal resistance
The most intuitive sign of aging – an increase in internal resistance, like burying a “resistance wire” inside a battery. When current passes through, the heat generated by Ohmic losses increases by the square of the internal resistance, while the capacity decay caused by aging is like a “fire extinguishing agent”, reducing the total energy that can be released. This contradictory interaction makes the thermal safety boundary of aging batteries elusive.
3 Empowering Battery “Body Temperature Monitoring” with Data
(1) Simplify complexity: from microscopic reactions to macroscopic thermal fields
The research team used a single particle model (SP) to simplify complex electrode reactions, assuming the porous electrode as a uniform sphere and focusing on the conservation of mass and energy balance during the lithium ion insertion process. Through simulation, it was found that the core area of cylindrical batteries becomes a “disaster area” for heat accumulation due to limited heat dissipation paths, with temperatures 10% -15% higher than the surface.
(2) Full factorial design: dismantling the “domino effect” of thermal runaway
Through 64 sets of simulation experiments, the study revealed the interactive effects of three core parameters:
Current rate (C-rate): Doubling the charging current (such as from 1C to 8C) increases the battery heating rate by three times. Under 8C fast charging, the temperature of some high-capacity batteries exceeds 90 ℃, reaching the thermal runaway warning threshold.
Internal resistance (R): For every 10 m Ω increase in internal resistance, the temperature rise rate at the same current increases by 15% -20%. Aging batteries with an internal resistance of 40 m Ω have a temperature 25 ℃ higher than new batteries during 3C charging.
Capacity (Q): Low capacity batteries (such as 1Ah) have a lower energy density and a smoother temperature rise; However, the additional heat generated by internal resistance of high-capacity batteries (5Ah) after aging far exceeds the heat dissipation advantage of capacity decay.
4 Battery aging thermal runaway warning
(1) Triple indicators for early warning
10% SOC low temperature anomaly: When the temperature of the battery exceeds 35 ℃ in a low charge state, the risk of thermal runaway increases by 40%, which is a sign that the SEI film begins to become unstable.
Sudden change in temperature rise rate: When dT/dt exceeds 0.2 ℃/s (especially at 50% SOC), it means that the internal reaction has entered the acceleration stage and immediate thermal management intervention is required.
Second derivative surge: When the temperature acceleration (d ² T/dt ²) exceeds 0.1 ℃/s ², it indicates that the thermal runaway chain reaction is difficult to suppress through natural heat dissipation and active cooling must be initiated.
(2) Accurate prediction of machine learning
Through logistic regression modeling, the research team found the critical threshold for internal resistance: under 3C charging conditions, when the internal resistance exceeds 35 m Ω, the probability of thermal runaway increases sharply from 5% to 65%. The model has an accuracy rate of 95% and can issue warnings 40 minutes in advance by monitoring internal resistance, current, and capacity in real-time, providing decision-making basis for battery management systems (BMS).
5 The aging paradox and thermal management challenges
A counterintuitive finding emerged in the study: the thermal runaway temperature of some aged batteries is higher than that of new batteries, because the gases released during the aging process weaken the reaction activity. But this does not mean that aging batteries are safer – the continuous heating caused by increased internal resistance actually leads to thermal runaway at lower SOC, increasing the concealment in practical applications.
Faced with this’ aging paradox ‘, the research team points out three major breakthrough directions:
Multi scale modeling: Integrating micro SEI film growth with macro thermal field distribution to construct a more accurate aging prediction model;
Active intervention strategy: dynamically adjust the charging strategy for high internal resistance batteries, such as segmented constant current charging to reduce temperature rise;
Material innovation: Developing temperature adaptive electrolytes to suppress exothermic reactions caused by aging from the source.
6 Conclusion
From mobile phones to cars, from the power grid to space, the “healthy lifespan” of lithium-ion batteries is not only related to performance, but also tied to the safety red line. This research is like a key, opening the mysterious black box between aging and thermal runaway, allowing us to see how battery “age” rewrites the thermal safety script at the microscopic level.
When batteries enter the “middle-aged and elderly” stage, the game between internal resistance and capacity never stops. In the future, with the integration of machine learning and real-time monitoring technology, perhaps we can customize a “personalized health profile” for each battery, making aging no longer a safety blind spot, but a predictable and manageable “growth trajectory”.
