Safety Vent Research Articles

Diagnosis of Abnormal Overcharge Internal Pressure in Lithium Battery Based on Physics‐Informed Neural Network's Residual Distribution

Changes in the internal pressure of lithium batteries often reflect the state of the batteries. Rapid diagnosis of abnormal internal pressure is importance for battery safety. This article proposes a battery overcharge internal pressure abnormality diagnosis method based on the detection of safety vent strain. First, this method establishes a multiphysical model between the strain of the battery's safety vent, surface temperature rise, and state of charge (SOC) under normal internal pressure. Second, a physics‐informed neural network is used to enhance the multiphysical model's accuracy. Third, the residual sequence generated from actual measurements and estimated values, along with an improved quartile range, is used to diagnose internal pressure abnormalities. Battery overcharge experiment results show that this method can diagnose internal pressure abnormalities within 260 s after overcharging and alarm. At this time, the battery has slight bulging, and the SOC is 102.1%. By conducting charging experiments under different conditions, the low false alarm rate of this method is only 0.575%. The proposed method can identify overcharging abnormalities before the lithium battery safety vent is opened, which greatly ensures the safe operation of the battery system.

Hot gas impingement and radiation on neighboring surfaces from venting and combustion in a package of 18650 cells

A quasi-steady, CFD-based modeling approach is employed to investigate the heat loading within a small package of twenty-five 18650 Li-ion cells. The quasi-steady approach allows for computationally efficient simulations to capture the compressible and turbulent flow field through the safety vent structure and out into the space surrounding a failing cell. Combustion of vent gases leads to high heat loading on neighboring cells and nearby surfaces. Heat transfer mechanisms within the enclosure include convection from hot gases, radiation from the participating medium, and radiation exchange between surfaces. Simulations provide insight into the magnitude of each heat transfer mechanism, and the spatial distribution of heat flux on nearby cells and surfaces within the pack. The complex geometry of the safety vent geometry resulted in an asymmetric jet flow pattern, which induces highly localized impingement heat transfer on specific cells within the enclosure. Radiation from hot surfaces was more significant than radiation from hot gases and soot to neighboring cells. The quasi-steady simulations may be used in the future to develop reduced-order heat transfer models that include the effects of venting and combustion on propagating failure.

Multi-model feature aggregation for classification of laser welding images with vision transformer

The laser welding technique is quite common in various manufacturing lines, including those for lithium-ion power batteries, due to its remarkable productivity, effectiveness, and flexibility. However, it has been observed that the consistency of the welding quality is not always optimal. This study investigates the adoption of laser welding in the manufacturing of lithium-ion batteries, such as their anode, cathode and safety vent, where consistent weld quality is crucial for battery performance and safety. Therefore, evaluating the laser-welding product is indispensable for industrial production and the public domain. Several techniques have been utilized for laser welding evaluation, both destructive and non-destructive. However, these methods are ineffective and too cumbersome to be adopted in mass manufacturing. In contrast, a machine vision strategy has recently been adopted to distinguish between successful and unsuccessful laser welding items. This opened new perspectives for evaluating the quality of the laser welding product using digital image techniques. However, these methods cannot deliver outstanding performance across multiple laser-welding products and achieve optimal classification accuracy. Deep learning has evolved remarkably in recent years and gained popularity in detecting welding defects. This paper presents the observation of a Hybrid Vision Transformer (HViT) to classify the laser welding images corresponding to their feature patch images based on multi-model feature aggregation. The VGG-16 and MobileNet, which were pre-trained on ImageNet, were utilized as the core models to extract the rich features of the laser welding image. To integrate these features, the squeeze excitation module (SE) was utilized, and a multi-layer perception (MLP) approach with a label smoothing optimizer was used for classification. To determine the effectiveness of the proposed strategy, a comparative analysis was conducted with a multitude of alternative machine learning and deep learning approaches. The results indicate that the proposed strategy surpasses all other methods in terms of classification accuracy and evaluation metrics on the test dataset.

Digital manufacturing in laser powder bed fusion of aluminium alloy safety feature for EV battery cell

Recently, a new way to produce prismatic Li-ion battery cell’s lid part for Battery Electric Vehicles (BEV) was presented, with integrated cell thermal management, based on the Laser Additive Manufacturing (LAM) method. In the solution, the safety vent protects the battery cell from unpredictable explosions caused by the increasing internal pressure. Additive manufacturing allows integrating the feature to the cell lid part and significantly decreases the process steps in manufacturing and increases the production efficiency. Aluminium powder materials for the used Laser Powder Bed Fusion (LPBF) method have relatively high tensile strength, which causes the need for minimum layer thickness for the safety vent. Reliability of producing such a thin layer as a gas tight structure is challenging and several procedures were studied. Material with lower tensile strength and higher elongation ability was tested during the second phase. The challenge is to produce such a thin wall thickness, which breaks at the pressure level of one MPa and opens the valve. The design is based on FEM analysis with constant equivalent strain theory to optimize safety vent dimensions. The pressure test was performed to measure the rupturing pressure of the thin aluminium LPBF layer as materials in normal mode and in annealed mode. The constant equivalent strain theory for estimate rupture pressure was in fine agreement with the experimentally measured ones, even with a maximum error rate. The results show that the manufacturing method is possible for such automotive mass production parts and when comparing different stacking strategies, it showed a great influence in the productivity of such parts’ production.

Thermal runaway-induced current interrupt device and vent activation behaviour in an 18650 lithium-ion battery cap using the Johnson-Cook criterion

Lithium-ion batteries (LIBs) thermal safety issues such as thermal runaway (TR) triggered by thermal or mechanical abuse have been one of the most important factors hindering its development at present. In order to effectively release the excessive pressure caused by TR, a safety vent is used as a reliable safety device in commercial LIBs. However, the current interrupt device (CID) and vent activation behaviour and mechanism are still unclear in the mesoscale. Herein, finite element simulations of metallic material deformation and failure during CID and vent activation at preset dynamic incremental pressure loads and various constant temperatures for a commercial 18650 LIB were carried out by introducing the Johnson-Cook (J-C) damage model in this study. The three-dimensional evolution, dynamical and mechanical analysis of the deformation to damage behaviour are quantitatively characterized. The CID- and vent-activation pressure based on the J-C damage criterion is significantly higher than the pressure value corresponding to the maximum von Mises stress. The results show fracture strain of the burst disk notch and plate will not exceed 0.93 % and 0.048 % respectively when the TR reaches the onset temperature. The temperature-dependent activation time reduction rate was developed to quantify the effect of temperature on the CID-and vent-activation times, indicating that TR temperature's effect on vent activation is significantly stronger than that of CID. These results may provide a reliable guide to LIB safety design.

CFD-Based Thermal Abuse Simulations including Gas Generation and Venting of an 18650 Li-Ion Battery Cell

A high-resolution, 3D, computational fluid dynamics (CFD) model was developed and implemented for simulating the heat and gas generation during thermal runaway failure of an 18650 Li-ion battery cell. The model accounts for volumetric gas generation within the active material of the cell and for gas flow through the jellyroll, into the headspace regions, through the safety vent, and out into the surrounding air space. The simulation captures the key features of the oven test, including: self-heating from decomposition reactions, initial venting (i.e. blowdown), temperature decrease due to evaporative cooling, thermal runaway, a second venting event associated with thermal runaway, and cooldown. The highly detailed geometric model of the safety vent allowed for new insight into the physics of venting during thermal runaway. Secondary flows, including ring vortices, counter-rotating vortex pairs, and corner vortices, were found to increase the rate of mixing of the vented gases with the surrounding air. The simulation was compared to previously reported experimental results and found to have good qualitative agreement of jet flow direction. The present thermal abuse model forms the basis for future studies to consider the role of gas impingement heat transfer and gas combustion in full battery pack propagating failures.

Heat transfer experiments and correlations for vent gases emerging from a Li-ion battery and impinging on a flat surface

During thermal runaway of Li-ion battery cells, high-temperature gas jets may impinge onto nearby surfaces and may increase the risk of a propagating failure. In this paper, heat transfer rates of jets emerging from a cylindrical Li-ion cell and impinging on a flat surface were measured experimentally and empirical correlations were developed based on the resulting data. Experiments used compressed air as the working fluid, which issued from the isolated safety vent and impinged on a target plate. Infrared thermography was used to obtain the spatially-resolved, convective heat transfer distribution on the target plate. While heat transfer distributions showed local maxima at the site of jet impingement, complex geometric features within the vent resulted in variation in the convection rate when comparing the multiple impinging jets emerging from a single Li-ion cell. Heat transfer correlations were developed in the form of Nusselt number as a function of Reynolds number and may be used in thermal runaway models which seek to include the effects of venting and combustion as an alternative to resolving the impingement heat transfer rates with expensive 3-D computational fluid dynamics simulations.

Quantification of heat energy leading to failure of 18650 lithium-ion battery abused by external heating

The presence of unavoidable extreme thermal fields, as well as frequent incidents of Lithium-ion battery (LIB) fires, emphasizes the importance of understanding the contribution of external heat energy to the degradation and failure of the LIB. In this study, we quantified the heat energy from the external heat source, heat transferred, and heat causing the safety vent crack to better understand the relationship between external thermal stress and LIB behavior during external heating tests. For experior data purposes, a series of external heating testing was performed with the NCA and LCO LIBs with 25–100% SOC. The external heat energy (qh) required to crack the safety vent varied between 92.70 and 232.80 kJ/m3 and 142.62–172.14 kJ/m3 for NCA and LCO, respectively. During venting at 25–100% SOC, the heat transferred for NCA and LCO were 56.77–136.07 kJ/m3 and 86.56–102.81 kJ/m3, respectively, representing 58.45–78.46% and 57.00–61.63% of the qh. Around 117.71–224.76 kJ/m3 and 181.10–218.59 kJ/m3 were produced by side reactions in NCA and LCO before the safety vent crack. The LIB's internal heat energy for breaking the safety disc (qsv) was estimated to be 174.49–360.83 kJ/m3 in NCA and 269.00–321.40 kJ/m3 in LCO. The qrec to qh ratio indicates that less qh may be required for the higher SOC LIB to enter stage II while the produced qgen reaches a maximum of 2 and 1.5 times that of qh for 100% NCA and LCO, respectively. During the breakout of the disc, the qsv exceeds the qh to about 2.4 and 1.9 times for 100% NCA and LCO, respectively. The findings of this study provide fundamentals on the thermal behavior of LIBs which can be used to understand the difference in hazard in transporting different types of LIBs, and decide how to implement designs for resisting thermal runaway propagation.

An analysis of gas-induced explosions in vented enclosures in lithium-ion batteries

Lithium-ion batteries (LIBs) have found wide usage and tremendous technological advancements in recent years, due to their numerous advantages, but the safe utilization of LIBs has been a major concern, which research, industry, and government agencies seek to address. During a LIB failure, a fire or explosion hazard may occur, depending on the failure mechanism, and safety vents can be designed to mitigate the explosion induced by gases released from LIBs in an enclosure. In the present study, explosion hazards of LIBs are analyzed, and a numerical model for gas explosion venting is developed and validated using experiments on hydrogen and methane explosions. Furthermore, the explosion characteristics of various hazardous gas mixtures emitted from LIBs at various equivalence ratios predicted by the model are compared to the NFPA 68 standards. The lithium‑cobalt oxide (LCO), lithium‑iron phosphate (LFP), lithium‑nickel‑cobalt‑aluminum oxide (NCA) and lithium‑nickel‑manganese‑cobalt oxide (NMC) batteries are used to determine the impact of battery chemistry, vent size, as well as the state of charge (SoC) of the batteries on the explosion characteristics. The impact of the equivalence ratio of the vented gas is also investigated as well as that of accounting for CO2 among the vented gas on the predicted peak pressure. In addition, the sensitivity of the explosion severity to variability in vented gas composition is also scrutinized.

What a role does the safety vent play in the safety of 18650-size lithium-ion batteries?

Herein, a series of experiments were performed to illustrate the impact of safety vents on the evolution of thermal runaway behaviors of 18650-size lithium-ion batteries. Meanwhile, the effect of safety vents on the thermal safety of batteries with different states of charge (SOC), i.e. 0%, 50% and 100% and cathode chemistries, i.e. lithium nickel manganese cobalt oxide (NMC), lithium cobalt oxide (LCO) and lithium iron phosphate (LFP) was explored. Compared with the battery with a safety vent, the thermal runaway behaviors of the battery in the absence of a safety vent are greatly worsened with ignition and thermal runaway occurring far earlier. As the battery SOC increases, it is demonstrated that the effect of the safety vent on battery thermal safety is reduced to some extent, with the difference in the times to thermal runaway between the batteries with and without a safety vent decreasing gradually. Besides that, it is found that the effect of the safety vent on the thermal runaway features of LFP-based batteries is relatively minor than in NMC-based batteries and LCO-based batteries. There is a linear-increasing relationship between the thermal runaway time difference and the mass loss difference for batteries with and without a safety vent.

High Resolution 3-D Simulations of Venting in 18650 Lithium-Ion Cells

High temperature gases released through the safety vent of a lithium-ion cell during a thermal runaway event contain flammable components that, if ignited, can increase the risk of thermal runaway propagation to other cells in a multi-cell pack configuration. Computational fluid dynamics (CFD) simulations of flow through detailed geometric models of four vent-activated commercial 18650 lithium-ion cell caps were conducted using two turbulence modeling approaches: Reynolds-averaged Navier-Stokes (RANS) and scale-resolving simulations (SRS). The RANS method was compared with independent experiments of discharge coefficient through the cap across a range of pressure ratios and then used to investigate the ensemble-averaged flow field for the four caps. At high pressure ratios, choked flow occurs either at the current collector plate when flow through the current collector plate is more restrictive or the positive terminal vent holes when flow through the current collector plate is less restrictive. Turbulent mixing occurred within the vent cap assembly, in the jets emerging from the vent holes, and in recirculating zones directly above the vent cap assembly. The global maximum turbulent viscosity ratio (μT/μ) of the MTI, LG MJ1, K2, and LG M36 caps at pressure ratio ofP1/P2= 7 were 4,575, 3,360, 3,855, and 2,993, respectively. SRS and RANS simulations showed that both velocity magnitude and fluctuating velocity magnitude were lower for vent holes which are obstructed by the burst disk. SRS showed high levels of fluctuating velocity in the jets, up to 48.5% of the global maximum velocity. The present CFD models and the resulting insights provide the groundwork for future studies to investigate how jet structure and turbulence levels influence combustion and heat transfer in propagating thermal runaway scenarios.

Impact of Charging and Charging Rate on Thermal Runaway Behaviors of Lithium-Ion Cells

The present work carries out a series of thermal runaway experiments to explore the impact of charging and charging rate on the thermal runaway behaviors of lithium-ion cells, in which five charging rates (0 C, 0.5 C, 1 C, 2 C and 4 C) and three initial states of charge (SOC), i.e. 25%, 50% and 75% are included. The thermal runaway process of 18650 lithium-ion cells induced by over-heating usually consists of seven stages, and is accompanied with high-temperature, fire and toxicity risks. The internal morphology of cells and the micro features of cell materials are seriously damaged after thermal runaway. Charging aggravates the thermal runaway behavior of cells, which is further exhibited as the earlier occurrence of safety vent opening, gas releasing and thermal runaway. Moreover, the severity deteriorates as the charging rate increases (the larger the charging rate, the earlier and more severe the thermal runway), which may be ascribed to the growth of cell SOC and the decline of cell stability under charging. This phenomenon is especially apparent for the cell with a high initial SOC where a more dramatic-rising α (the advancement ratio of critical times for thermal runaway due to charging) is observed.

Develop an Activation Pressure Measurement Method of the Safety Vent and Investigate the Relationship between Cell Safety Devices' Activation Pressure and LIB Cell Safety

The current interrupt device (CID) and vent mechanism in the Cylindrical cells are a fuse-type safety device that permanently disconnects the cell's electrical circuit and releases internal pressure when triggered by excessive cell pressure by abnormal conditions to keeps the cell safe from the thermal runaway risks. Compared to the importance of the safety devices' activation pressure, the test method and apply the techniques to the cell characterization was not defined adequately.This research developed the test methods, procedures, and equipment to measure the activation pressure accurately of both the CID and vent mechanism simultaneously. We select four different cell markers' commercial 18650 cell models with about 3.5 Ah nominal capacity to evaluate the cell model's safety level and to identify the relationship between the activation pressure level and the safety test item: electrical, mechanical, environmental (Thermal) abnormal impacts.To investigate the relationship between cell safety devices' activation pressure and the cell model's safety, we performed some cell safety tests and cell model design checks. The cell alignment check with the electrode gap measurement, including some electrical tests, checks the test samples' quality status. Cell safety tests include thermal safety, external short circuit, nail penetration, impact, and crush test. Each safety test item's test condition and procedure are referenced from widely accepted cell safety standards and battery industrial best practices for the lithium-ion battery.The activation pressure of the CID and vent mechanism was measured simultaneously by detecting the cell voltage changes and applied pressure to vent, respectively. All four cell models have shown that the CID was always activated earlier at a lower pressure than the vent mechanism. The activation pressure of the CID and the vent mechanism of the four cell models were different by manufacturers. The tolerance and the activation pressure gap between CID and the vent mechanism of each cell model were different among the four cell models.The cell safety test items can be classified by 1) thermal and electric abuse test and 2) mechanical abuse test. We used the EUCAR Hazard Level to evaluate the safety level of each test item items. The table explains each test item's safety level of the four cell models according to the EUCAR Hazard Level criteria. The cell hazard levels of the thermal and electric abuse test items (thermal safety and external short circuit test) are strongly affected by the activation pressure level of the CID and vent mechanisms. The detailed investigation concluded that the CID's activation pressure level affects more than that of the vent mechanism to the thermal and electric abuse test items' hazard level. These results are derived from the fact that the safety device activates in advance at a lower pressure than the cell enclosure's opening.Meanwhile, the cell hazard levels of the mechanical abuse test items (nail penetration, impact, and crush test) were not affected by the safety devices' activation pressure level. Because the mechanical abuse test items always opened the cell enclosure in advance compared to the safety device activation.This research proposes to add the activation pressure level of the cell safety devices to the EUCAR Hazard Level criterion to enhance the efficiency of evaluating the cell models' hazard level. That can provide more worthy criteria for the cell selection and cell safety evaluation process for the multi-cell battery system design. Figure 1

Dynamics of Explosions in Cylindrical Vented Enclosures: Validation of a Computational Model by Experiments

Recent explosions with devastating consequences have re-emphasized the relevance of fire safety and explosion research. From earlier works, the severity of the explosion has been said to depend on various factors such as the ignition location, type of a combustible mixture, enclosure configuration, and equivalence ratio. Explosion venting has been proposed as a safety measure in curbing explosion impact, and the design of safety vent requires a deep understanding of the explosion phenomenon. To address this, the Explosion Venting Analyzer (EVA)—a mathematical model predicting the maximum overpressure and characterizing the explosion in an enclosure—has been recently developed and coded (Process Saf. Environ. Prot. 99 (2016) 167). The present work is devoted to methane explosions because the natural gas—a common fossil fuel used for various domestic, commercial, and industrial purposes—has methane as its major constituent. Specifically, the dynamics of methane-air explosion in vented cylindrical enclosures is scrutinized, computationally and experimentally, such that the accuracy of the EVA predictions is validated by the experiments, with the Cantera package integrated into the EVA to identify the flame speeds. The EVA results for the rear-ignited vented methane-air explosion show good agreement with the experimental results.

A Lightweight Multiscale Attention Semantic Segmentation Algorithm for Detecting Laser Welding Defects on Safety Vent of Power Battery

At present, in order to improve the safety performance of power battery, a safety vent is welded on the battery cover to avoid unpredictable explosions. It is vital to detect the laser welding defects on safety vent effectively for product quality. In this paper, a lightweight multiscale attention semantic segmentation algorithm with high accuracy and efficiency was proposed. We built an experimental dataset of safety vent welding defects with a total of 7263 original images, which were collected from a battery manufacturing production line. The main framework of the proposed model consists of four modules: the improved Res2Net serving as the feature extraction sub-module, an attention mechanism, a localization block and a boundary anti-aliasing module. This architecture can segment defects of different sizes and shapes in real-time and get more refined segmentation results simultaneously. To evaluate the method, experiments concerning mean IOU and pixel accuracy were conducted, and an average validation accuracy of 99.4% and the mean IOU of 84.67% were achieved respectively. Furthermore, comparison experiments using some outstanding algorithms on safety vent’s welding defects test dataset were performed. It proves that our method achieved the best performance in terms of model size, computational complexity, efficiency and detection accuracy. Specifically, the model size is only 3.8 MB, and the frames per second (FPS) is 132.3. In brief, the proposed model is suitable for laser welding quality detection on safety vent in an industrial environment. Additionally, our study can provide a reference for designing relevant defect detection tasks using semantic segmentation method.

Coupled damage variable based on fracture locus: Prediction of ductile failure in a complex structure

This article focuses on predicting the instant of failure in a real scale component of complex geometry and loading using a ductile damage model calibrated exclusively on small-scale laboratory specimens of relatively simple shape. The ductile behaviour of a strain hardened aluminium alloy AA1050, formed into a thin-walled component, is modelled by a coupled ductile fracture locus model presented in a recent study (Baltic et al., 2020). The component is exposed to high internal pressure and has a safety vent designed for safe pressure handling. The extensive plastic deformation in the safety vent leads to localised ductile failure occurring at a limit load. The pertaining material parameters were calibrated solely from basic ductile fracture experiments in the preceding work (Baltic et al., 2020), where the bottom section of the thin-walled component was machined into notched and shear samples to characterize different states of stress and to construct a well-defined fracture locus. Although the calibrated material model relies on the local fracture strain measurements, it involves a regularization as a function of the length scale defined as a width of the observed localisation band from Digital Image Correlation (DIC) analysis. In the current study the calibration on small-scale specimens is complemented by a large-scale specimen to determine the length scale correction crucial for capturing the correct width of the localisation band in the analysed structure. This is necessary because the failure initiation zones of the calibration specimens and the real size structure, i.e. their gauge lengths where the localisation band appears, vastly differ in size. Finite element (FE) model results are compared to measurements of the deformation of the aluminium component under pressure and maximum load prior to failure. The numerical and experimental results show an excellent agreement and consistent fracture predictions for various mesh discretizations.

A lightweight deep learning algorithm for inspection of laser welding defects on safety vent of power battery

With the wide applications of power battery in the automobile industries, the safety of power battery is becoming an increasingly prominent problem. At present, a safety vent welded on the battery plate could prevent unpredictable explosions. To perform quality control, the inspection of laser welding defects on safety vent is a critical issue. In this paper, based on the theory of convolutional neural network (CNN) and the technique of transfer learning, a pre-trained SqueezeNet model with small model size and low computation complexity was proposed. We totally collected 34537 images from the production line, and built a 2-classifications dataset and a 7-classifications dataset respectively. It proves that our proposed model achieved better accuracy than the other six contrastive CNN models in these two classification tasks. Specifically, it obtained an accuracy of 99.57 % in the 2-classifications task and an accuracy of 95.58 % in the 7-classifications task. Besides, the model features lightweight and high-speed with only 1.2 MB model size and 4.9 ms average test time; so, it is more suitable for welding quality inspection of safety vent in an industrial production line. Additionally, we ported our pre-trained SqueezeNet and the other four contrastive models to Raspberry Pi embedded system to evaluate their response time. Our proposed model has achieved well response time of less than 330 ms. Our experiments indicate that the proper CNN model can help to conduct the laser welding quality inspection tasks that are usually performed by humans.

Comparative Study on Thermal Runaway Characteristics of Lithium Iron Phosphate Battery Modules Under Different Overcharge Conditions

In order to study the thermal runaway characteristics of the lithium iron phosphate (LFP) battery used in energy storage station, here we set up a real energy storage prefabrication cabin environment, where thermal runaway process of the LFP battery module was tested and explored under two different overcharge conditions (direct overcharge to thermal runaway and overcharge to safety vent open-standing–recharge to thermal runaway). In this experiment, surveillance cameras, infrared imagers, temperature detectors, and gas detectors were used to guarantee all-around online observation. The experimental results show that under the conditions of these experiments, stop the overcharging process in time after the first battery safety vent is opened can effectively suppress the further development of thermal runaway, and maintain a safe state within 2 h. It also indicates that the thermal runaway process of LFP battery module changes with heat accumulation which needs reaction time, if the heat accumulation could be stopped in time, the occurrence of thermal runaway accidents would be avoided. This provides effective theoretical guidance for safety warning and fire protection of electrochemical energy storage stations with LFP battery system.

Reliability of Cylindrical Li-ion Battery Safety Vents

Cylindrical Li-ion batteries (cells) typically have safety vents in the positive terminal to enable the release of gases that build up inside the battery and thus help reduce the effects of thermal runaway, including fire and explosion. However, the vents are not always effective, and it is critical to understand why. This paper overviews various vent designs and presents two case studies of vents in cylindrical Li-ion batteries that failed to operate properly. The first case study concerns a Sony VCT5 18650 Li-ion battery in which thermal runaway caused the cylindrical casing (can) to rupture. The second case study involves an Ampking 20700 Li-ion battery in which thermal runaway caused side-wall rupture of the casing. In both cases, the vents did not function as intended. Computed tomography (CT) scanning was used to investigate the internal structure of the battery to assess the failure mechanisms of the failed vents. These cases raise concerns about the efficiency, reliability, and safety of some current vent designs.

Li-Ion Battery Fire Hazards and Safety Strategies

In the past five years, there have been numerous cases of Li-ion battery fires and explosions, resulting in property damage and bodily injuries. This paper discusses the thermal runaway mechanism and presents various thermal runaway mitigation approaches, including separators, flame retardants, and safety vents. The paper then overviews measures for extinguishing fires, and concludes with a set of recommendations for future research and development.