There is a need to understand the impacts of trigger mechanism and cell format on thermal runaway heat output in order to improve testing capabilities and better inform thermal models. This study examines thermal runaway heat output for three different cell formats as a function of trigger mechanism. The trigger mechanisms considered are heaters, internal short circuiting device, and nail penetration. Specifically, the thermal runaway responses for the KULR 18650-K330, KULR 21700-K500, LG 21700-M50, and Saft D-Cell-VES16 are examined. All experiments are conducted inside a Fractional Thermal Runaway Calorimeter (FTRC).

The propensity for a cell design to experience can side wall rupture (SWR) during thermal runaway is highly influenced by how a battery design mechanically constrains its cells. Testing cells while unsupported has been found to yield false negative results that don't represent this risk in a battery configuration. This talk addresses how to verify the adequacy of battery design measures used to control SWR and how to get results relevant, accurate, and statistically defendable for a proposed battery design. 

Understanding the risks associated with thermal runaway of LIBs is critical for designing safe cells and battery systems. The thermal response of cells can greatly vary for identical cell designs tested under identical conditions, the distribution of which is costly to fully characterize experimentally and cannot be captured by deterministic models. The Battery Failure Databank contains robust, high-quality data from hundreds of abuse tests spanning numerous commercial cell designs and abuse testing conditions. Data was gathered using a fractional thermal runaway calorimeter and contains the fractional breakdown of heat and mass from ejected and non-ejected cell contents, as well as high-speed radiography of the internal structural response of cells during thermal runaway. This presentation will provide an overview of the Battery Failure Databank as well as insights gained from in-situ radiography of internal causes of outlier battery failure events.

We present a numerical model to study cell venting, internal pressure, and gas-release in Li-ion cells undergoing thermal runaway. A k-ϵ Reynolds-Averaged Navier-Stokes (RANS) model is adopted to describe the turbulent flow out of the cells, while the fluid dynamics inside the cells is described by Darcy-Forchheimer’s equation. A series of computational fluid dynamics (CFD) simulations are conducted at various states-of-charge to study propagation.

Understanding the fractional heat output of a thermal runaway event is only half of the solution to designing safer, and more reliable, battery packs. This study bridges the gap between FTRC data acquisition and application by examining a thermal model of a cell pack on the the xEMU Portable Life Support System (PLSS). Four cells, the MJ1, Samsung 30Q, LG 3.35Ah NBV, and Sony VTC6, were selected for analysis to show the variation in system response to cells with different fractional allocations.

This poster introduces a test facility using a simplified mini-module setup for the investigation of the reproducibility of Thermal Propagation (TP). This facility, as well as each individual experiment and set of experiments, have been optimized to generate a simplified, highly reproducible testing environment and testing execution to answer the question whether multiple tests of TP yield chaotic inconsistent results or if they can be statistically described.

Lithium-ion batteries are prevalent in every aspect of modern life. For all applications, the battery safety is an important consideration. Limited research has been conducted to characterize prismatic cells with their unique challenges including how electrode gapping, electrolyte degradation, or lithium plating affect the safety. A systematic study is reported here on prismatic cells cycled at different temperatures and the safety aspect of the cells is evaluated using accelerating rate calorimetry.

Lithium-ion batteries are nowadays used for a broad range of applications, especially medium sized cylindrical cells, resulting in a variety of requirements and usage conditions. Those conditions are represented in experiments by different calendar and cyclic aging parameters. When the cells reach SOH 80%, the aging is stopped and the cells are subsequently analyzed in Accelerating Rate Calorimeters (ARC) with the Heat-Wait-Seek method (HWS). The results of these experiments allow to assess the impact of the aging on the safety of the cell.

Despite safer battery material, battery thermal management could be a key to safer post Lithium technology. Na0.53MnO2 & Na3V2(PO4)3/C based materials as cathode and coconut shell-derived hard carbon as anode were studied in this work. The safety related parameters including the heat generation during charging and discharging and thermal abuse tests have been executed by the means of sophisticated calorimetry instruments.

Thermal runaway (TR) in Li-ion batteries refers to uncontrollable exothermic reactions triggered by elevated temperatures. As the temperature of the battery rises, the exothermic reactions further heat up the cell, creating a positive feedback cycle. Despite recent safety monitoring advances in battery management systems (BMS), the prevention of thermal runaway remains a challenge. The talk will provide insights into delaying/mitigating TR in large format Li-ion cells using NOHMs advanced electrolytes.

This presentation shows the setup and results of three different thermal runaway triggers on modern battery cells in a custom-made TR reactor. It focuses on the trigger overtemperature, overcharge and nail-penetration. The investigated cell types are state-of-the-art automotive cells. The results are discussed in three main categories: thermal behavior, ventgas production and ventgas composition. The findings are supposed to be valuable for battery pack designer, testing institutions and regulations. 

Packaging technologies company PACT, LLC will present Thermo Shield™, a paper-based, fire-resistant shipping wrap designed to prevent catastrophes caused by battery explosions during transport. By suppressing fumes or gasses from escaping and limiting external oxygen supply, the 100% recyclable solution can suppress thermal runaway and propagation at temperatures up to 800°C, and restrict the temperature outside the wrap to 80°C.

Industry standards provide a minimum level of safety and performance for cells and batteries, but they are only the minimum and can be lacking in fully identifying design issues that can result in field safety incidents and performance concerns.

Mechanically induced internal short circuit is reviewed.  Mechanical damages inside the cells were investigated systematically using progressive indentation and x-ray computed tomography (XCT).  Failure mechanisms of multiple layers were proposed. Parameters such as load, displacement, cell voltage and surface temperature have been collected for machine learning analysis. A thermal runaway database is being built to rank and predict safety risks of various Li-ion batteries.

Thermal Runaway has been an increasing concern with lithium based cells and batteries transported using the various means of transport. Studies are underway to define protocols to test shipping packages containing lithium based cells and batteries to confirm their safety during transportation. In a parallel effort, the UL team has conducted studies to characterize the efficacy of various materials to mitigate thermal runaway propagation or contain the worst case fire created inside a package due to thermal runaway. The results of the studies will be presented.

Li-ion battery thermal runaway is a critical safety issue in electric vehicles and an early warning for battery failure is required. Since gas venting is often a precursor of thermal runaway, the gas detection method will be the focus of this talk. The composition of battery vent-gas during a thermal runaway event includes CO, CO₂, H₂, and volatile organic compounds (VOCs).  After evaluating battery vent-gas compositions at different conditions and checking available sensors, the Non-Dispersive Infrared (NDIR) CO₂ sensor is selected due to its robustness and cost-effectiveness.

Multi-functional venting units are used to enable battery pack breathing during regular operation, and for fast pressure relief in case of gas evolution inside the pack, e.g. by Thermal Runaway. The flammable gas mixtures exiting the battery system can be ignited by hot particles ejected from destroyed cells, causing fire. The presentation will highlight a new solution how to prevent hot particles from being ejected from the battery pack, thus reducing the risk of gas ignition.

KULR Technology Group has received two US Department of Transportation (DoT) special permits for the transport of recycled battery and prototype lithium batteries up to 2.1KWh. The permit provides exceptions from shipping papers and employee training when shipping lithium batteries up to 2.1 KWh. The permit authorizes the exceptions based on using KULR’s specially designed thermally protective packaging which incoporates the Company’s patented thermal runaway shield (TRS) technology. Prototype lithium batteries are only authorized to be transported on cargo carrying aircrafts to, from or within the US when approved by DoT. KULR will present its TRS packaging solution.

2019 Chemistry Nobel Prize winning technology, Li-ion batteries are the energy storage device of choice; however, the limited theoretical capacity hampers its wide adaption in many applications. Li metal batteries (LMBs) encompassing a lithium metal anode with sulfur/layered oxide-based cathode material (Li-S and Li-NMC532) provide a sustainable possibility to improve energy/power density. However, thermal safety and overall stability issues continues to hinder its use in practical applications. In spite of the significant effort to alleviate the cycle life of LMBs, the thermal safety aspects of these systems remain unknown, therefore could lead to thermal runaway under extreme conditions. This talk will provide an understanding of the thermal stability of LMBs from materials level to cell level. The amount of exothermic heat generated for Li-NMC (2.9 KJ/g) and Li-S (188 J/g) from the coin cell DSC analysis shows amplified safety risk in Li-NMC532 batteries.

We established a machine-learning assisted modeling methodology for prediction of battery safety risk. Based on a mechanical model and experimental results, we generate a sufficient dataset consisting of strain states and their corresponding safety risks, covering both cylindrical and pouch cells, various states of charges, and loading conditions. We apply machine-learning tools combined with the established finite element mechanical model to predict the safety risks of the cells.

We introduce a deep learning-based battery health prognostics approach to predict the whole degradation trajectory together with the end-of-life point and knee-point, ensuring the safe and reliable operation of battery systems. The model requires no external feature engineering and no further retraining for the same cell type in different stages of life. The computing efficiency has been improved 15 times compared with the current iterative prediction approaches. The processor-in-the-loop tests confirm that the model has an outstanding performance with as little as 100 cycles of data.

Many automakers have dealt with the battery safety issue by enclosing the batteries into protective cases to prevent nail penetration and deformation during the car crash. But with the range of electric vehicles increasing and the size of the batteries, a more detailed understanding of battery behavior under abuse becomes necessary. Simulation (a.k.a CAE) tools that predict the response of a Li-ion battery pack to various abusive conditions can support analysis during the design phase and reduce the need for physical testing. The physics is quite complex however, involving mechanical deformation, electrochemistry and thermal reactions. It spans length scales with orders of magnitude differences between critical events, internal shorts happening at the millimeter level, triggering thermal runaway of the complete battery. This presentation will give an overview of the computational challenges associated with battery crash and discuss the various tools introduced by LS-DYNA to address them.