Unlocking the thermal safety evolution of lithium-ion batteries under shallow over-discharge

Zhang, Guangxu; Wei, Xuezhe; Chen, Siqi; Zhu, Jiangong; Han, Guangshuai; Dai, Haifeng

doi:10.1016/j.jpowsour.2022.230990

Cited by 35 publications

(12 citation statements)

References 27 publications

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“…Most researchers have concluded that the aging process slows down at low SOCs (Hahn et al, 2018;Naumann et al, 2018). However, discharging the battery below 0% SOC can cause the terminal voltage to decrease, resulting in performance and safety issues (Chen et al, 2021;Zhang et al, 2022). For instance, Yao et al (Yao et al, 2019) and Guo et al (Guo et al, 2016) indicate that dropping the terminal voltage of the battery well below the 0% SOC defined operation range (to values such as 0.2 V) may result in loss of electric contact, transition metal dissolution, and current collector corrosion, all of which lead to calendar aging.…”

Section: Li-ion Batteries and Calendar Agingmentioning

confidence: 99%

Assessment of the calendar aging of lithium-ion batteries for a long-term—Space missions

et al. 2023

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Energy availability is a critical challenge for space missions, especially for those missions designed to last many decades. Space satellites have depended on various combinations of radioisotope thermoelectric generators (RGTs), solar arrays, and batteries for power. For deep space missions lasting as long as 50 + years, batteries will also be needed for applications when there is no sunlight and RTGs cannot support peak power demand due to their insufficient specific power. This paper addresses the potential use of lithium-ion batteries for long-term space missions. Using data collected from the literature and internal experiments, a calendar aging model is developed to assess the capacity fade as a function of temperature, state-of-charge and time. The results for various LIB chemistries are used to identify the best candidate chemistries and determine the conditions, with a focus on low temperatures, that can best enable deep space missions.

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Section: Li-ion Batteries and Calendar Agingmentioning

confidence: 99%

Assessment of the calendar aging of lithium-ion batteries for a long-term—Space missions

et al. 2023

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“…In EV applications, cell performance is highly dependent on operating conditions. Under abuse conditions, such as over-charging [3] or over-discharging [4], battery voltage can move beyond their safe operating windows, which can accelerate degradation and increase the risk of battery failure after long-term incubation. Accurate estimation of battery state-of-charge (SOC) under various operating conditions is critical for effective battery management in both large-scale EVs [5] and photovoltaic-assisted applications [6].…”

Section: Introductionmentioning

confidence: 99%

Spatial-Temporal Self-Attention Transformer Networks for Battery State of Charge Estimation

et al. 2023

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Over the past ten years, breakthroughs in battery technology have dramatically propelled the evolution of electric vehicle (EV) technologies. For EV applications, accurately estimating the state-of-charge (SOC) is critical for ensuring safe operation and prolonging the lifespan of batteries, particularly under complex loading scenarios. Despite progress in this area, modeling and forecasting the evaluation of multiphysics and multiscale electrochemical systems under realistic conditions using first-principles and atomistic calculations remains challenging. This study proposes a solution by designing a specialized Transformer-based network architecture, called Bidirectional Encoder Representations from Transformers for Batteries (BERTtery), which only uses time-resolved battery data (i.e., current, voltage, and temperature) as an input to estimate SOC. To enhance the Transformer model’s generalization, it was trained and tested under a wide range of working conditions, including diverse aging conditions (ranging from 100% to 80% of the nominal capacity) and varying temperature windows (from 35 °C to −5 °C). To ensure the model’s effectiveness, a rigorous test of its performance was conducted at the pack level, which allows for the translation of cell-level predictions into real-life problems with hundreds of cells in-series conditions possible. The best models achieve a root mean square error (RMSE) of less than 0.5 test error and approximately 0.1% average percentage error (APE), with maximum absolute errors (MAE) of 2% on the test dataset, accurately estimating SOC under dynamic operating and aging conditions with widely varying operational profiles. These results demonstrate the power of the self-attention Transformer-based model to predict the behavior of complex multiphysics and multiscale battery systems.

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“…The energy crisis and environmental pollution drive the continuous transformation of energy structurex . Green and renewable energy has become the common goal pursued in the new era. , Lithium-ion batteries stand out among numerous candidates as the most promising energy storage devices. − To date, lithium-ion batteries, due to their high energy and long cycle life, have been widely applied in transportation, energy storage stations, and portable electronics and especially in electric vehicles. − …”

Section: Introductionmentioning

confidence: 99%

Revealing the Impact of Fast Charge Cycling on the Thermal Safety of Lithium-Ion Batteries

Zhang

Wei

Chen

et al. 2022

ACS Appl. Energy Mater.

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The safety of the degraded lithium-ion batteries has an essential impact on second life application. This study systematically investigates the thermal safety changes of lithium-ion batteries after deep aging under the fast charge aging path and reveals the degradation mechanisms caused by fast charge cycling. Lithium plating is the primary degradation mechanism, which thickens the solid electrolyte interface film, causes the loss of active lithium and electrolyte, and leads to a significant increase in impedance and a dramatic decrease in capacity. Therefore, compared with the fresh cells, the heat generation rate increases, while the total heat generation is reduced for aged cells. Besides, the thickened solid electrolyte interface film has lower thermal stability, decreasing the self-heating temperature for aged cells. Furthermore, thermal runaway results of partial cells prove that fast charge cycling reduces the thermal stability of the anode, which further proves that the thermal runaway-triggering temperature decrease is the result of the combination of the anode–electrolyte and anode–cathode reactions. Moreover, fast charge cycling reduces the lithium plating potential upon overcharging, which leads to the occurrence of side reactions in advance, creating the ratio of side reaction heat increase of aged cells for thermal runaway triggering. In addition, the loss of active materials reduces the maximum temperature and maximum temperature rise rate of the aged cell. The findings can provide references for battery safety management system optimization and safer battery screening.

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Unlocking the thermal safety evolution of lithium-ion batteries under shallow over-discharge

Cited by 35 publications

References 27 publications

Assessment of the calendar aging of lithium-ion batteries for a long-term—Space missions

Assessment of the calendar aging of lithium-ion batteries for a long-term—Space missions

Spatial-Temporal Self-Attention Transformer Networks for Battery State of Charge Estimation

Revealing the Impact of Fast Charge Cycling on the Thermal Safety of Lithium-Ion Batteries

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