Prismatic Lithium-ion Batteries Research Articles

Internal Short Circuit and Dynamic Response of Large-Format Prismatic Lithium-Ion Battery Under Mechanical Abuse

Abstract Prismatic lithium-ion batteries (LIBs) are becoming the most prevalent battery type in electric vehicles, and their mechanical safety is garnering increased attention. Understanding the mechanical response and internal short circuit (ISC) of prismatic LIBs during dynamic impact is important for enhancing the safety and reliability of electric vehicles. Thanks to the pioneer's works on the cylindrical and pouch LIB, prismatic LIB can draw on relevant experimental and numerical modeling methods. However, there is still a lack of research on the dynamic effects of prismatic LIB in various loading directions. To address this disparity, the current research utilizes quasi-static and dynamic impact experiments on prismatic LIBs as a foundation. First, the mechanical response of a sizable prismatic LIB under quasi-static conditions and the dynamic effects are examined when subjected to mechanical abuse from various loading directions. Second, an anisotropic finite element model that considers dynamic strain rates are developed, enabling it to accurately represent the mechanical response to both quasi-static and dynamic impact loads. At last, we performed an analysis of ISC occurring under dynamic loading conditions combining the experimental and simulated results. The experimental results as well as the established model can provide reference for the safe design, application, and analysis of prismatic LIBs.

Thermal management for the prismatic lithium-ion battery pack by immersion cooling with Fluorinated liquid

Thermal management for the prismatic lithium-ion battery pack by immersion cooling with Fluorinated liquid

Series arc-induced internal short circuit leading to thermal runaway in lithium-ion battery

With the widespread implementation of battery energy storage systems (BESSs), significant attention has been focused on issues involving electrical safety. The series arc hazard caused by loose connectors between batteries has become a serious problem. However, research findings for the evolution process of the series arc and the related hazard principle are still unclear. Therefore, in this study we focus on the series arc at the negative terminal of a 20 Ah prismatic lithium-ion battery, establish an experimental platform for the arc, and conduct research on the hazards process. Our results indicate that the arc can induce the thermal failure of the battery when the power supply voltage is 300 V and the circuit current is 15 A. Through a battery voltage analysis, computed tomography scans, and jellyroll disassembly, we uncover the evolution process and hazard laws of series arcs and clarify the failure pathways of arc-induced battery faults. The hotspots formed by arc melt the casing and cause electrolyte leakage. In addition, the heat transfer from the battery terminal to the jellyroll induces separator melting and internal short circuits in batteries. These cause an internal short circuit between the anode and the cathode, as well as combustion of the leaked electrolyte, which give rise to distinct thermal runaway behavior under different states of charge. By comparing runaway behavior with failures triggered by external heating, we clarify that the series arc is a novel risk factor that induces failure. This study addresses the gap in research related to arc effects on battery safety. This is crucial to the development of safe battery systems that do not present arc hazards.

Experimental and Modeling Study of Arc Fault Induced Thermal Runaway in Prismatic Lithium-Ion Batteries

With the widespread application of electrochemical energy storage technology, the safety issues of lithium-ion batteries have garnered significant attention. The issue of arc faults resulting from electrical failures is especially critical, as it can lead to catastrophic battery disasters. Therefore, this paper first established an arc testing platform and conducted experiments on top cover and body of prismatic lithium-ion batteries to analyze the thermoelectric characteristics between arc and battery. Under experimental conditions of 300 V and 15 A, it was found that arcs can induce thermal runaway in batteries. Subsequently, based on the experimental conditions, a mathematical model was established to induce thermal runaway in batteries through an equivalent method of arc heat source. By comparing the temperature curves of model and experiment, the RMSE of temperature at the center point of large surface was 5.09 °C (with a maximum temperature of 212 °C), indicating the accuracy of the model. This paper’s research on arc faults in battery systems revealed the evolution pattern and realized that arcs can trigger thermal runaway in batteries. The model for arc-triggered thermal runaway in batteries is highly accurate, capable of reducing the number of experiments, accelerating experimental progress, and is of significant importance for guiding the design of arc experiments about batteries.

Thermal runaway front propagation characteristics, modeling and judging criteria for multi-jelly roll prismatic lithium-ion battery applications

Large-format prismatic Li-ion batteries (LIBs) are prominent energy storage devices in electric transportation applications. However, large-format LIB induces severe thermal runaway (TR) disasters. Battery failure commonly initiates from a local point of one jelly roll and then propagates to the whole cell, called thermal runaway front (TRF) propagation. This study investigates the TRF propagation mechanism of multi-jelly roll-based LIBs through experiments, modeling, and theoretical analysis for thermal runaway propagation (TRP) mitigation. Experiments prove that battery venting changes along the jelly roll-safety valve directions during the TRF boundary movement. Besides, TRF propagation speed is found to be accelerated inside each cell (from 3.6 to 10.6 mm/s) during TRP, driven by a significant temperature gradient, chemical reactions, and gas flow along the TRP direction. The in-cell TRF acceleration behavior is more noticeable for batteries with more jelly rolls. The TRF speed-jelly roll index equations are proposed to reveal the propagation acceleration principle mathematically. Furthermore, a thermal-physical model is developed to precisely simulate in-cell TRF propagation behavior, which is validated by experimental data. Moreover, the TRF boundary temperature equation and “No TRP” judging criteria are proposed through theoretical analysis. This study proposes promising strategies for potential TRP suppression, contributing to future safe battery system design.

An online evaluation model for mechanical/thermal states in prismatic lithium-ion batteries under fast charging/discharging

Conventional online evaluation methods for the mechanical/thermal behaviour of lithium-ion batteries fall short in terms of efficiency and accuracy, especially under extreme conditions coupling high-temperature and fast charging/discharging. This paper proposes an electrochemical/thermal/mechanical analytical model for prismatic lithium-ion batteries to assess their temperature, stress, deformation, and gas evolution. An electrochemical submodel is formulated, covering the lithium intercalation/deintercalation, solid-electrolyte interphase (SEI) decomposition/regeneration, and electrolyte decomposition. A thermal submodel is created to simulate heat transfer between the cell and its environment, considering reaction and Joule heating as heat sources. A mechanical submodel is developed to reveal the effects of nonlinear elastic constitutive properties and the mechanical/thermal/electrical states on cell deformation and stress, incorporating the reaction gas evolution. A coupled multidisciplinary analytical model is formed, using the state variables of temperature, stress, and deformation to link the submodels. The model's performance was validated against numerical and experimental results under high-temperature charge/discharge cycle conditions, demonstrating efficiency at the level of seconds, temperature errors below 0.6 %, and pressure errors below 4.6 %. The advantages in efficiency, accuracy, and applicability highlight its excellent prospects in energy storage and electric vehicle applications.

The capacity degradation path prediction for the prismatic lithium-ion batteries based on the multi-features extraction with SGPR

Accurate capacity degradation path estimation of lithium-ion batteries plays a crucial role in ensuring the safety and reliability of electric vehicles. In recent years, the evolution of the status of health (SOH) prediction with machine learning techniques has become a research hotspot because of its powerful computing power and robustness. Thus, this study employes the sparse gaussian process regression (SGPR) data-driven approach with multi-features extracted from the battery cycling processes to project the potential degradation patterns of the lithium-ion batteries. Firstly, a battery life test platform was built. The accelerated life aging tests of batteries at different temperatures (25 °C, or 60 °C) and different discharge rates (1C, or 2C) were conducted to establish the dataset for the multi-features extraction and training of the SGPR algorithm. Secondly, different battery characteristic features were extracted based on the battery cycle charge-discharge curves. Various order-reduction treatments, i.e., the filter-based, embedding-based, and fusion-based selection algorithms, were performed to suppress the over-fitting and improve the estimate's accuracy. Finally, using the extracted features as inputs, SGPR models are constructed to estimate the degradation path of the battery. With the 50 % training data, the SGPR has a higher estimation accuracy than the regular GPR, and the average maximum absolute errors for the batteries are 2.80 %, 1.22 %, 3.57 %, and 1.83 %, respectively.

Experimental and simulation investigation for prismatic lithium-ion battery cells under impact loading

In the current work, prismatic lithium-ion battery (LIB) cells were impacted in various rigid cylinder loading speeds (v = 1, 5, 10, 2000 and 5000 mm/s), which provided the data basis for establishing a practical and reasonable LIB cell damage assessment method. Based on thermal-runaway cell safety borders (TCSB) and undamaged cell safe borders (UCSB), the deformed cells can be classified into safe, risk and failure regions. With the increment of the v values, the UCSB and TCSB of cells decreased linearly along a logarithm axis. Moreover, the relationships between key cell parameters (cell thickness, separator thickness and separator fracture strain) and the cell deformation limits (DL) under rigid cylinder impact loads were also revealed. A DL prediction method was newly introduced for the prismatic LIB cells with different sizes. Finally, the tensile mechanical data of cell components (anodes, cathodes and separators) were also measured for cell local detailed simulation models. By the simulations, the effect of the frictional behaviors between cell components on the deformation processes and failure mechanisms of LIB cells were deeply discussed.

Application of machine learning in ultrasonic diagnostics for prismatic lithium-ion battery degradation evaluation

Lithium-ion batteries are essential for electrochemical energy storage, yet they undergo progressive aging during operational lifespan. Consequently, precise estimation of their state of health (SOH) is crucial for effective and safe operation of energy storage systems. This paper investigates the viability of ultrasound-based methods for assessing the SOH of prismatic lithium-ion batteries. In the experimental framework, a designated prismatic lithium-ion battery was subjected to numerous charging and discharging cycles using a battery cycling system. Subsequently, ultrasonic detection experiments were conducted to record the waveforms of the transmitted and received signals. These signals were then processed through wavelet transforms to extract signal amplitude and time-of-flight data. To analyse these data, we applied four algorithms: linear regression, support vector machines, Gaussian process regression, and neural networks. The predictive performance of each algorithm was evaluated through extensive experimentation and analysis. The combination of ultrasonic signals with computational models has emerged as a robust technique for precise battery degradation assessment, suggesting its potential as a standard in battery health evaluation methods.

Thermal Performance Analysis of a Prismatic Lithium-Ion Battery Module under Overheating Conditions

Thermal runaway (TR) of lithium-ion batteries has always been a topic of concern, and the safety of batteries is closely related to the operating temperature. An overheated battery can significantly impact the surrounding batteries, increasing the risk of fire and explosion. To improve the safety of battery modules and prevent TR, we focus on the characteristics of temperature distribution and thermal spread of battery modules under overheating conditions. The heat transfer characteristics of battery modules under different battery thermal management systems (BTMSs) are assessed. In addition, the effects of abnormal heat generation rate, abnormal heat generation location, and ambient temperature on the temperature distribution and thermal spread of battery modules are also studied. The results indicate that the BTMS consisting of flat heat pipes (FHPs) and bottom and side liquid cooling plates can effectively suppress thermal spread and improve the safety of the battery module.

Exploring the electrochemical and mechanical properties of lithium-ion batteries in salt spray environments

With the pressing need to expedite the transition toward a greener marine industry, energy-efficient and eco-friendly lithium-ion batteries (LIBs) are increasingly favored. However, compared to land applications, marine environments pose unique challenges to the utilization of LIBs, thereby necessitating targeted safety measures. In this study, prismatic LIBs (PLIBs) are subjected to standard salt spray tests to emulate marine environments, and the resultant morphological changes and external voltage response of the batteries under the corrosion behavior are analyzed. Subsequently, the impacts of the salt spray environment on the electrochemical performance of PLIBs are assessed through a range of characterization techniques including scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), and charge-discharge test. Finally, quasi-static ball indentation tests are carried out on the corroded batteries to study the behaviors under mechanical abusive loading scenarios. Results reveal that the most prominent effect of the salt spray environment on the batteries is the occurrence of swelling, attributable to the imperfect sealing of the battery tabs. This study represents an innovative exploration of the viability of LIBs in the marine environments, providing fundamental theoretical guidance for early detection of battery corrosion and collision risks, as well as facilitating protective design considerations.

Monitoring of Thermal Runaway in Commercial Prismatic High-Energy Lithium-Ion Battery Cells via Internal Temperature Sensing

The temperature of a lithium-ion battery is a crucial parameter for understanding the internal processes during various operating and failure scenarios, including thermal runaway. However, the internal temperature is comparatively higher than the surface temperature. This particularly affects cells with a large cross-section, which is due to heat development within the cell and lower heat dissipation due to a poorer ratio of volume to surface area. This paper presents an approach that enables real-time monitoring of the behavior of a commercial prismatic high-energy battery cell (NMC811/C, 95 Ah, Contemporary Amperex Technology Co., Limited (Ningde, China)) in the event of thermal runaway induced by overcharging. The internal cell temperature is investigated by the subsequent integration of two hard sensors between the two jelly rolls and additional sensors on the surface of the aluminum housing of the battery cell. The sensor’s signals show a significant increase in the temperature gradient between the temperature in the core of the cell and the cell casing surface until the onset of venting and thermal runaway of the battery. The data enable a detailed investigation of the behavior of the battery cell and the comparatively earlier detection of the point of no return in the event of thermal runaway.

A numerical and statistical study to determine the effect of thermophysical properties of phase change material for lithium-ion battery thermal management

Lithium-ion batteries’ performance is quite sensitive to temperature, leading to capacity fade, acceleration of aging effect, and possible thermal runaway. The temperature of lithium-ion batteries increases under operating conditions of high discharge rates. The heat released by the battery can be effectively removed using phase change material (PCM). The thermophysical properties of the PCM affect the heat removal performance of the PCM. In this study, the effect of thermophysical parameters such as thermal conductivity, latent heat, specific heat, and density on maximum battery temperature and battery temperature uniformity was numerically investigated. The dominant factors for PCM to prevent temperature increase in a prismatic LiMn2O4 lithium-ion battery were identified by orthogonal design to improve the thermophysical properties of PCM. The thermophysical properties of PCM were changed by incorporating the expanded graphite. Based on what was observed in the current study, the influence of the thermal conductivity of PCM was higher than other thermophysical properties, while the influence of the latent heat on both maximum battery temperature and temperature uniformity was negligible. Density was the second crucial factor that could help reduce the maximum battery temperature and keep the temperature distribution uniform. The results obtained from this study can allow the design of effective battery thermal management systems by improving the thermophysical properties of the PCM.

Battery Venting Caused By Fast Charging

Lithium-ion batteries (LIBs) experience high risks of failure during unreasonable fast charging. Various degradation mechanisms inside the LIBs such as lithium (Li) plating, solid electrolyte interphase growth and electrolyte dry-out can undermine the electrochemical performance and induce massive gas generation alongside the operation. As a typical failure behaviour, venting occurs when the internal pressure of battery cell exceeds the safety threshold, releasing the gaseous products as well as depressurizing the cell. Recent studies1–3 of thermal runaway (TR) tests after fast charging have found that accumulated plated Li can react with electrolyte at elevated external temperatures, decreasing both self-heating and onset temperatures of TR. Yet, how fast-charging degradation will affect battery venting behaviours remains unclear.To answer this question, in this study, a series of fast charging experiments under controlled cooling as well as adiabatic TR tests were conducted with 51 Ah LiNi0.6Mn0.2Co0.2O2/graphite prismatic LIBs. The results showed that the prismatic battery underwent severe Li plating with over 30% capacity fade after 10 cycles of 4C charging. In the adiabatic TR tests, the aged batteries after 4C charging exhibited lower self-heating temperature and venting temperature as compared to the fresh batteries, by 51 ℃ and 34.4 ℃ respectively. This can be explained by the additional gas generation from the reaction between plated Li and electrolyte in the fast-charged batteries. Gas analyses of 120 ℃ hot-box tests for the degraded anodes with the electrolyte showed that the vented gas at the early venting stage primarily consisted of carbon dioxide, carbon monoxide and ethylene. The same charging protocols were then conducted in a natural convection thermal chamber with poor heat dissipation, where the temperature rise was much higher than those under forced convection as expected. Excessive cycling operations with off-limit charge rates (5C and 5.6C) were observed to directly cause battery swelling and venting without TR, and the temperature decreasing rates during rest after each charging process tend to slow down and even remain stable during a certain period of time. This indicates that the exothermic reaction between plated Li and electrolyte can be directly triggered by fast charging if heat removal is not effective enough. The findings provide useful insights into battery venting induced by fast charging, which can shed light on battery safety evaluation for fast charging techniques.Acknowledgements:This work is supported by the Faraday Institution BESAFE project (FIRG038), the Imperial College President’s PhD Scholarship Scheme (funded by EPSRC), the National Natural Science Foundation of China (Grant No. 52207241), China National Postdoctoral Program for Innovative Talents (grant no. BX20220171), China Postdoctoral Science Foundation (grant no. 2022M711760), and Shuimu Tsinghua Scholar Program (grant no. 2021SM130).

Thermal mapping analysis of a 48V prismatic lithium-ion battery pack with active and passive cooling

This experimental study investigates the thermal behavior of a 48V lithium-ion battery (LIB) pack comprising three identical modules, each containing 12 prismatic LIB cells, during five charge-discharge cycles. A homogeneous liquid cooling system is applied at the bottom of the modules to control the pack temperature when it reaches 40°C (active cooling phase). The initial two cycles represent passive cooling, where the cooling liquid remains stationary. Temperature distribution is measured and analyzed using 27 thermocouples, providing insights into temperature changes in the cells, modules, pack, and cooling system inlet/outlet. Results show that in passive cooling cycles, minimum temperature occurs at pack surfaces due to better convective heat transfer, while maximum temperature is observed in the central LIB cells. The active cooling phase alters the temperature distribution within the pack. One module is found to be more sensitive to high currents, generating more heat and releasing it faster. Additionally, the positive tab temperature is higher than the negative tab temperature within a single cell. The liquid cooling system decreases the temperature rise from 5.8°C to 3.5°C in the discharge cycles with a constant current of -237A. This study emphasizes the significance of evaluating the thermal behavior of individual modules and highlights the complexity of the LIB pack system, as well as the impact of an indirect liquid cooling system on enhancing its thermal performance.

A transient multi-path decentralized resistance-capacity network model for prismatic lithium-ion batteries based on genetic algorithm optimization

Battery thermal management is crucial for preventing the safety issues of lithium-ion batteries. Due to the simple modeling and fast calculation speed, the thermal resistance-capacity (RC) network model is broadly applied in the design of battery thermal management systems. However, the simplification of heat flow paths and the lumped definition of thermal capacity in traditional RC models result in large temperature prediction errors, which fail to reflect the thermal response in complex and diverse heat transfer situations. To improve the prediction accuracy, a decentralized centroid multi-path RC network model is constructed for a typical prismatic lithium-ion battery. This novel model incorporates multiple heat flow paths with additional thermal resistances and legitimately decentralizes the lumped heat capacity to other surface center points, resulting in a more realistic thermal response. A genetic algorithm is employed to determine the unknown thermal resistances and heat capacities at the attributed nodes. Results show that compared to the traditional RC network model, the multi-path decentralized RC network model can reduce the temperature prediction error from 4.24 to 0.95 ℃. This more refined modeling approach extends the application scope of thermal resistance network models to more complex scenarios while maintaining efficient simulation speed, which enables the attainment of more accurate and reliable onboard temperature predictions for lithium-ion power systems.

Nanofluid-based cooling of prismatic lithium-ion battery packs: an integrated numerical and statistical approach

Nanofluid-based cooling of prismatic lithium-ion battery packs: an integrated numerical and statistical approach

Modelling for the mitigation of lithium ion battery thermal runaway propagation by using phase change material or liquid immersion cooling

In this study, a three-dimensional (3D) thermal runaway (TR) model with conjugate heat transfer submodel is adopted. TR behaviors for a battery pack with 12 prismatic lithium-ion batteries (LIBs) are then simulated. Three thermal safety measures of TR protection from internal shorting in Cell 1 to pack level configuration are compared and evaluated. Paraffin phase change material (PPCM) is firstly proposed to delay the TR propagation between LIBs with solid-liquid phase change as heat transfer mechanism. Different thicknesses of PPCMs are compared to verify the TR mitigation performance of the PPCM under thermal abuse condition. The TR time for the Cell 2 is delayed to be 64 s, 266 s and 414 corresponding to PPCM thickness of 1.8 mm, 3.6 mm and 5.4 mm. As the simulation results shows, this TR time can be further delayed to 798 s by a strategy with combing PPCM with insulation. In addition, this work proposes a novel thermal safety protection based on immersion cooling with pool boiling of fluorinated liquid as heat transfer mechanism. We observe that the average temperature of Cell 2 - Cell 12 tends to be within 34 °C under immersive cooling condition, which indicates the possibility to prevent the TR.

Mechanical and Optical Characterization of Lithium-Ion Battery Cell Components/Cross-Ply Lamination Effect

Excessive mechanical loading of lithium-ion batteries can impair performance and safety. Their ability to resist loads depends upon the properties of the materials they are made from and how they are constructed and loaded. Here, prismatic lithium-ion battery cell components were mechanically and optically characterized to examine details of material morphology, construction, and mechanical loading response. Tensile tests were conducted on the cell case enclosure, anodes, cathodes, and separators. Compression tests on stacks of anodes, cathodes, separators, and jellyrolls were made from them. Substantially differing behaviors were observed amongst all components tested. An optical examination of the anodes, cathodes, and separators revealed homogeneities, anisotropies, and defects. Substantial texturing was present parallel to the winding direction. When highly compressed, jellyrolls develop well-defined V-shaped cracks aligned parallel to the texturing. Like many laminates, altering the lay-up construction affects jellyroll mechanical performance. To demonstrate, a cross-ply jellyroll was fabricated by rotating every other complete component set (cathode/separator/anode/separator), reassembling, and compressing. A distinctly different fracture pattern and increased compressive strength were observed.

Numerical optimization of the cooling effect of a bionic fishbone channel liquid cooling plate for a large prismatic lithium-ion battery pack with high discharge rate

Numerical optimization of the cooling effect of a bionic fishbone channel liquid cooling plate for a large prismatic lithium-ion battery pack with high discharge rate