Battery Failure Research Articles

Synergistic enhancement of cathode/anode interfaces with high water-retentive organohydrogel enabling highly stable zinc ion batteries

Current aqueous battery electrolytes, including conventional hydrogel electrolytes, exhibit unsatisfactory water retention capabilities. The sustained water loss will lead to subsequent polarization and increased internal resistance, ultimately resulting in battery failure. Herein, a double network (DN) organohydrogel electrolyte based on dimethyl sulfoxide (DMSO)/H2O binary solvent was proposed. Through directionally reconstructing hydrogen bonds and reducing active H2O molecules, the water retention ability and cathode/anode interfaces were synergistic enhanced. As a result, the synthesized DN organohydrogel demonstrates exceptional water retention capabilities, retaining approximately 75% of its original weight even after the exposure to air for 20 days. The Zn||MnO2 battery delivers an outstanding specific capacity of 275 mA h g−1 at 1 C, impressive rate performance with 85 mA h g−1 at 30 C, and excellent cyclic stability (95% retention after 6000 cycles at 5 C). Zn||Zn symmetric battery can cycle more than 5000 h at 1 mA cm−2 and 1 mA h cm−2 without short circuiting. This study will encourage the further development of functional organohydrogel electrolytes for advanced energy storage devices.

A study of expansion force propagation characteristics and early warning feasibility for the thermal diffusion process of lithium-ion battery modules

Research on thermal runaway warning and thermal propagation mechanism is of great importance for improving the thermal safety of lithium-ion batteries. This article focuses on the battery modules and examines the feasibility of using expansion force as thermal runaway warning signals. Results show that the utilization of the expansion force can detect battery failure 1314.61 s earlier and provide thermal runaway warnings 26 s earlier compared to that of temperature. This suggests that the use of the expansion force at the battery module level still shows good feasibility. In addition, the fluctuation mechanism of the expansion force during thermal propagation is further discussed by conducting experiments on the thermal propagation of modules with different sizes. Experimental results show that the superposition effect of adjacent battery expansion forces is the main influencing factor causing expansion force changes with two peaks. The fluctuation mechanism of expansion force can characterize the gas discharge behaviors of thermal runaway at different stages, such as the opening of pressure relief valves and multi-stage gas discharge during thermal runaway.

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.

Polyacrylonitrile Based Triblock Copolymer Binder Enabling Excellent Performance toward LiNi0.5Mn1.5O4 and Sulfur Based Batteries.

There is an urgent need for lithium-ion batteries with high energy density to meet the increasing demand for advanced devices and ecofriendly electric vehicles. Spinel LiNi0.5Mn1.5O4 (LNMO) is the most promising cathode material for achieving high energy density due to its high operating voltage (4.75 V vs Li/Li+) and impressive capacity of 147 mAh g-1. However, the binders conventionally used are prone to high potential and oxidation at the cathode side, resulting in a loss of the ability to bond active material and conductive agent integrity. This can lead to severe capacity fading and irreversible battery failure. This study demonstrates that incorporating acrylic anhydride and methyl methacrylate into conventional acrylonitrile through solution polymerization improves the binding energy and voltage resistance. The results indicate that the triblock poly(acrylonitrile-methyl methacrylate-acrylic anhydride) (PAMA) binder has a much higher peeling strength (0.506 N cm-1) compared to its polyvinylidene fluoride (PVDF) counterpart (0.3 N cm-1), making it a more feasible strategy. When assembled with LiNi0.5Mn1.5O4, the PAMA based electrode maintains a capacity retention of 70.7% after 800 cycles at 0.1 C, which is significantly higher than the 33.9% retention of the PVDFbased electrode. This is due to the large number of polar groups, including ─C≡N and ─C═O, on PAMA, which are conducive to adsorbing lithium polysulfide. The S@PAMA electrode is tested and maintained a capacity value of 628.7 mAh g-1 after long-term cycling, confirming its ability to effectively suppress the shuttle effect.

Interfacial Domino Effect Triggered by β-Alanine Cations Realized Highly Reversible Zinc-Metal Anodes.

Realizing durative dense, dendrite-free, and no by-product deposition configuration on Zn anodes is crucial to solving the short circuit and premature failure of batteries, which is simultaneously determined by the Zn interface chemistry, electro-reduction kinetics, mass transfer process, and their interaction. Herein, this work unmasks a domino effect of the β-alanine cations (Ala+) within the hydrogel matrix, which effectively triggers the subsequent electrostatic shielding and beneficial knock-on effects via the specifical adsorption earliest event on the Zn anode surface. The electrostatic shielding effect regulates the crystallographic energetic preference of Zn deposits and retards fast electro-reduction kinetics, thereby steering stacked stockier block morphology and realizing crystallographic optimization. Meanwhile, the mass transfer rate of Zn2+ ions was accelerated via the SO4 2- anion immobilized caused by Ala+ in bulk electrolyte, finally bringing the balance between electroreduction kinetics and mass transfer process, which enables dendrite-free Zn deposition behavior. Concomitantly, the interfacial adsorbed Ala+ cations facilitate the electrochemical reduction of interfacial SO4 2- anions to form the inorganic-organic hybrid solid electrolyte interphase layer. The above domino effects immensely improve the utilization efficiency of Zn anodes and long-term stability, as demonstrated by the 12 times longer life of Zn||Zn cells (3650 h) and ultrahigh Coulombic efficiency (99.4 %).

Interfacial Domino Effect Triggered by β‐Alanine Cations Realized Highly Reversible Zinc‐Metal Anodes

AbstractRealizing durative dense, dendrite‐free, and no by‐product deposition configuration on Zn anodes is crucial to solving the short circuit and premature failure of batteries, which is simultaneously determined by the Zn interface chemistry, electro‐reduction kinetics, mass transfer process, and their interaction. Herein, this work unmasks a domino effect of the β‐alanine cations (Ala+) within the hydrogel matrix, which effectively triggers the subsequent electrostatic shielding and beneficial knock‐on effects via the specifical adsorption earliest event on the Zn anode surface. The electrostatic shielding effect regulates the crystallographic energetic preference of Zn deposits and retards fast electro‐reduction kinetics, thereby steering stacked stockier block morphology and realizing crystallographic optimization. Meanwhile, the mass transfer rate of Zn2+ ions was accelerated via the SO42− anion immobilized caused by Ala+ in bulk electrolyte, finally bringing the balance between electroreduction kinetics and mass transfer process, which enables dendrite‐free Zn deposition behavior. Concomitantly, the interfacial adsorbed Ala+ cations facilitate the electrochemical reduction of interfacial SO42− anions to form the inorganic‐organic hybrid solid electrolyte interphase layer. The above domino effects immensely improve the utilization efficiency of Zn anodes and long‐term stability, as demonstrated by the 12 times longer life of Zn||Zn cells (3650 h) and ultrahigh Coulombic efficiency (99.4 %).

Fault diagnosis method for lithium-ion batteries based on the combination of voltage prediction and Z-score

ABSTRACT Safety accidents in new energy electric vehicles caused by lithium-ion battery failures occur frequently, and the timely and accurate diagnosis of failures in battery packs is crucial. Voltage, as one of the primary characterization parameters of lithium-ion battery malfunctions, is widely utilized in fault diagnosis. This article proposes a lithium-ion battery fault diagnosis method Fault diagnosis method based on the combination of voltage prediction and Z-score. Firstly, the stable trend component is extracted from the battery voltage data using variational mode decomposition, which avoids the influence of noisy signals and random perturbations to the greatest extent. Subsequently, a TCN-BiLSTM-attention model is designed to estimate the average voltage of the battery under normal conditions. Finally, the residuals between the estimated and individual cell voltages are calculated, and the Z-score is utilized to locate and judge whether the battery is caused by the occurrence of a fault. Through verification with real vehicle data and experimental data, the proposed method effectively identifies abnormal battery cells. Compared to the correlation coefficient method, this approach exhibits superior applicability.

In situ nanoscale insights into the interfacial degradation of Zn metal anodes

Zn metal batteries are highly attractive because of their high theoretical specific capacity, intrinsic safety and resource availability. However, further development is significantly hindered by low Coulomb efficiency, which is closely linked to reaction processes occurring at electrode/electrolyte interfaces. Herein, we have achieved a real-time visualization and comprehensive analysis of the interfacial evolution of Zn metal anode via in situ AFM in organic and aqueous electrolytes, respectively. The processes of uneven nucleation, dendrite growth, the ZnO formation and the dissolution of Zn substrate are directly probed in aqueous electrolyte, which induces interfacial deterioration and ultimately results in battery failure. In organic electrolyte, the in situ observations show that the homogeneous nuclei form on the Zn surface to induce the dendrite-free deposition, however, exhibiting poor Zn plating/stripping reversibility. This work delves into the dynamic evolution and electrochemical behaviors regulated by solvents, which provides in-depth understanding of structure-reactivity correlations and further interfacial engineering.

An Efficient FEniCS implementation for coupling lithium-ion battery charge/discharge processes with fatigue phase-field fracture

Accurately predicting the fatigue failure of lithium-ion battery electrode particles during charge–discharge cycles is essential for enhancing their structural reliability and lifespan. The fatigue failure of lithium-ion battery electrode particles during charge–discharge cycles poses a significant challenge in maintaining structural reliability and lifespan. To address this critical issue, this study presents a mathematical formulation for fatigue failure in lithium-ion batteries, utilizing the phase-field approach to fracture modeling. This approach, widely employed for fracture failure analysis, offers a comprehensive framework for capturing the complex interplay between mechanical deformation, chemical lithium concentration, and crack formation. Specifically, an additive decomposition of the strain tensor is employed to account for the swelling and shrinkage effects induced by lithium diffusion. Moreover, open-source code (https://github.com/noiiG) is provided, constituting a convenient platform for future developments, e.g., multi-field coupled problems. The developed chemo-mechanical model undergoes fatigue failure package is written in FEniCS as a popular free open-source computing platform for solving partial differential equations in which simplifies the implementation of parallel FEM simulations. Several numerical simulations with two different case studies corresponding to monotonic charge process and fatigue charge/discharge process are performed to demonstrate the correctness of our algorithmic developments.

Wireless Data Acquisition System with Feedback Function

When operating solar–wind power plants (SWPPs) located in populated areas, cases of premature failure of expensive batteries and other power equipment often occur. The purpose of this study is to develop a wireless data acquisition system (DAS) for the operation of an SWPP with a feedback function to prevent material damage from the failure of power equipment and to increase the efficiency of natural energy use. The principles of constructing a DAS, free from some of the disadvantages of analogues, are described in this paper. Intelligent wireless current and voltage sensors and a device for receiving and recording data with an additional feedback function have been developed, providing real-time feedback when the measured parameters go outside the norm. Measurement data are displayed on the laptop screen and alphanumeric display and stored on the hard drive along with timestamps and current event messages. An example of using a reverse communication channel to implement the functions of backup battery protection and to switch SWPP loads is described. The principles and methods proposed in this article are suitable for constructing systems for remote measurements of any physical quantities; therefore, the scope of application of the described system can be significantly expanded.

Determination traction-separation parameters and its sensitivity analysis of bilinear cohesive zone model through experimental and numerical peeling analysis of electrodes

The optimization of traction-separation parameters within the cohesive zone model (CZM) is crucial for accurately simulating electrode peeling failure in lithium-ion batteries. This study performed 180° peeling tests on NCM electrodes and used Abaqus software alongside the sim-flow optimization tool for simulation analysis, aiming to accurately replicate the failure behavior at the lithium-ion battery electrode interface. Experimental results were used to determine the fracture energy of the electrode interface, while numerical simulations analyzed the peeling performance of the electrode. By fitting the force-displacement curves from both simulation and experiment, the traction-separation parameters within the bilinear CZM were optimized. Additionally, the study analyzed the effects of traction-separation parameters, as well as the modulus and thickness of the current collector, on peeling behavior. The results showed that a significant increase in the interface stiffness and strength increased the steady-state peeling force. Among these, the fracture energy had the most significant influence on the steady-state peeling force. Furthermore, while the modulus and thickness of the current collector affected the maximum peeling force, their effect on the steady-state peeling force was negligible. These findings enhance the accuracy of simulating the failure behavior of the electrode interface.

Adsorption performance and fitting of thermal runaway gases in power batteries on CuO-doped SnS monolayer: A DFT study

Thermal runaway failure of power batteries will release a large amount of thermal runaway gas (TRG), causing serious environmental pollution and safety accidents. Therefore, monitoring TRG is crucial to battery safety. In this paper, the adsorption capacity of TRG on SnS monolayer and SnS-CuO monolayer are compared based on DFT. SnS-CuO monolayer exhibits strong adsorption for C2H4 and CO. Compared with the SnS monolayer, the Eads are improved by 285.10 % and 527.24 %, respectively. Meanwhile, the electron affinity of TRG strongly correlates with adsorption properties (SSE < 0.06, R-square > 0.9, and RMSE < 0.2), indicating that it plays a significant role in explaining the adsorption characteristics of different TRG. Furthermore, the dielectric constant of the solvent exhibits a stronger correlation with the adsorptive properties of TRG (R-square > 0.96 and RMSE < 0.004), indicating the environmental tunability of TRG adsorption. In general, this research reveals the potential of SnS-CuO monolayer as a gas sensor for C2H4 and CO and provides theoretical guidance for exploring the impact of various TRG and solvent environments on the adsorption performance of SnS-CuO monolayer. It is expected to be widely used in TRG monitoring of power batteries in the future.

Performance of interstitial thermal barrier materials on containing sidewall rupture and thermal runaway propagation in a lithium-ion battery module

Containing thermal runaway propagation in lithium-ion battery packs is a pertinent problem that is exacerbated when considering high energy density batteries and severe battery failure modes, such as sidewall rupture. This work investigates five different passive thermal barrier materials for their performance with respect to containing sidewall rupture and mitigating thermal runaway propagation between high energy density 21,700 cells. Along with propagation rate and total count of sidewall rupture failures, two new key performance indicators are introduced, the temperature reduction value and the sidewall rupture ratio, to quantify a material's performance. Overall, a stainless steel thermal barrier coated with an intumescent flame-retardant fabric performs best out of the five materials investigated. Evidence is given for the count of sidewall ruptures being linearly correlated to the propagation rate. It is shown that cells that fail with sidewall rupture have an average maximum surface temperature of 919 °C compared to 653 °C for cells that fail with top cap rupture. Evidence is also presented that sidewall rupture propagates to adjacent cells in a module. This work aims to provide battery pack designers with information to aid them in determining a strategy for containing thermal runaway propagation and sidewall rupture, including a method to evaluate the performance of thermal barrier materials against this objective.

Influence of ambient temperature on multidimensional signal dynamics and safety performance in lithium-ion batteries during overcharging process

Ambient temperature significantly influences the safety performance of lithium-ion batteries (LIBs), particularly their thermal runaway (TR) behaviors. Yet, the complexities of multidimensional signal dynamics in overcharged LIBs under different ambient temperatures are not well understood. In this study, we performed comprehensive overcharging abuse tests under cold (-10 °C and 0 °C), normal (20 °C), and high ambient temperatures (60 °C), to investigate the evolution of multidimensional signals of expansion force, gas concentration, surface temperature, and voltage. Results show that TR events are not triggered at ambient temperatures of −10 °C and 0 °C, with the maximum temperatures and corresponding rise rate reaching only 125 °C and 0.5 °C/s, respectively. In contrast, for batteries undergoing TR, the maximum temperatures and rates of temperature increase peaked at 410.3 °C and 20.6 °C/s, respectively. The ambient temperature has a minimal impact on the venting force of the battery, which varies from approximately 9500 N to 10000 N, primarily driven by an increase in internal gas pressure during overcharging—a factor relatively unaffected by temperature changes. After safety valve activation during overcharging, Hydrogen (H2) is consistently the first gas detected immediately across all ambient temperature scenarios. Additionally, an increase in ambient temperature results in earlier detection of abnormal expansion and venting behaviors, characterized by lower venting voltages and higher venting temperatures. This study contributes to a deeper understanding of battery failure mechanisms under various ambient temperatures and informs the development of early safety warning strategies for LIBs during the charging process.

Effects of Electrolyte Solvent Composition on Solid Electrolyte Interphase Properties in Lithium Metal Batteries: Focusing on Ethylene Carbonate to Ethyl Methyl Carbonate Ratios

This study investigated the influence of variations in the mixing ratio of ethylene carbonate (EC) to ethyl methyl carbonate (EMC) on the composition and effectiveness of the solid electrolyte interphase (SEI) in lithium-metal batteries. The SEI is crucial for battery performance, as it prevents continuous electrolyte decomposition and inhibits the growth of lithium dendrites, which can cause internal short circuits leading to battery failure. Although the properties of the SEI largely depend on the electrolyte solvent, the influence of the EC:EMC ratio on SEI properties has not yet been elucidated. Through electrochemical testing, ionic conductivity measurements, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy, the formation of Li2CO3, LiF, and organolithium compounds on lithium surfaces was systematically analyzed. This study demonstrated that the EC:EMC ratio significantly affected the SEI structure, primarily owing to the promotion of the formation of a denser SEI layer. Specifically, the ratios of 1:1 and 1:3 facilitated a uniform distribution and prevalence of Li2CO3 and LiF throughout the SEI, thereby affecting cell performance. Thus, precise control of the EC:EMC ratio is essential for enhancing the mechanical robustness and electrochemical stability of the SEI, thereby providing valuable insights into the factors that either enhance or impede effective SEI formation.

Safety risk assessment for automotive battery pack based on deviation and outlier analysis of voltage inconsistency

Safety risk assessment is essential for evaluating the health status and averting sudden battery failures in electric vehicles. This study introduces a novel safety risk assessment approach for battery systems, addressing both cell and pack levels with three key indexes. The core of the assessment lies in representing the relative deviation of cell voltages through scatter diagrams across various stages of service life. Specifically, the study quantifies voltage deviations and deviation angles within different state of charge intervals to gauge safety risks at the cell level. Leveraging clustering algorithms aids in identifying outlier values. Furthermore, the dispersion of scatter points is utilized to assess safety risks at the pack level. Validation of this proposed model is conducted through cycling tests on battery modules with a deformed cell, demonstrating its efficacy in capturing inconsistent features of mechanical deformation abuse across the three indexes, thereby triggering alarms during operation. Moreover, the method is applied to assess the safety risks of five hazardous and accident-prone vehicles, enabling comprehensive evaluation of potential faulty cells and safety risks at the pack level. This proposed approach offers a fresh perspective on the comprehensive safety risk assessment of battery systems.

A failure risk assessment method for lithium-ion batteries based on big data of after-sales vehicles

Accurate prediction of battery failure has always been a challenge in the field of electric vehicles. In existing prediction methods, battery current, voltage and temperature of a single vehicle sample are often analyzed as the main characteristic parameters, however, the independent analysis of these parameters can hardly achieve the early warning of battery failure. This paper proposes a failure risk assessment method based on big data analysis, which can evaluate the failure risk level of the battery pack in advance. Specifically, the characteristic parameters strongly related to battery failure are extracted through the correlation analysis of after-sales data. Then, the synthetic minority oversampling technique is employed to expand the number of failure samples for model training. Finally, the vehicle risk coefficient prediction model is established by the random forest algorithm. According to the prediction results of field data of extensive vehicles, the model can successfully pick out the high-risk vehicles before battery failure, occupying roughly 7% of all vehicles, which is of great value for engineering application. In practical application, these vehicles with high-risk coefficient can be paid more attention by companies, so as to further ensure the driving safety of vehicle users.

Quantitative failure analysis of lithium-ion batteries based on direct current internal resistance decomposition model

Accurate failure analysis plays a pivotal role in the optimization design and lifetime prediction of 4.45 V high-voltage LiCoO2/Graphite (LCO/Gr) batteries. Multiphysics coupling model brings great opportunities to conduct battery failure analysis quantitatively, although it is quite challenging because many model parameters need to be handled properly. Herein, we systematically elaborate the differences of ion and electron transport properties before and after cycling ageing of LCO/Gr batteries by constructing direct current internal resistance (DCR) decomposition model. The key parameters acquisition method is established, and the mechanism of DCR growth is elucidated. Furthermore, the aforementioned model parameters are refined by using a hybrid power pulse characteristics (HPPC) curve optimization algorithm based on DCR decomposition results obtained from the three-electrode battery system. Through analyzing the influence of single-factor parameter ageing on battery voltage output capacity and discharge temperature rise, the main factors affecting battery failure process are identified. For instance, the account of the positive electrochemical reaction resistance related to the kpos increased from the initial 22.9% of total DCR to 37.3% after ageing. This work provides a reliable quantitative analysis basis for the global optimization design of advanced LIBs.

Untapped Potential of Fluoride Ions in Maximizing the Electrochemical Stability of Deep Eutectic Solvents.

Advancing batteries is pivotal to propelling our society toward a sustainable, electrified future. The stability of the electrolytes forms the backbone of energy storage systems. This is particularly the case for redox flow batteries (RFBs). Their deployability depends on their longevity and dependability. The presence of unstable electrolytes can trigger undesirable reactions, degrade performance, and lead to battery failure. Aqueous electrolytes, with limited electrochemical stability window (ESW), are prone to hydrogen and oxygen evolution. Conversely, nonaqueous electrolytes offer enhanced stability. In this study, we unveil the ESW of a nonaqueous eutectic solvent, comprising choline fluoride and ethylene glycol─a composition that has eluded experimental investigation until now. Our findings show that the stability window, reduction, and oxidation potential limits of deep eutectic solvents are sensitive to variations in the halide component of the ammonium salt. This work not only highlights the benefits of novel deep eutectic solvents but also sets the stage for their strategic use in future battery electrolytes.

The Burgeoning Zinc Powder Anode for Aqueous Zinc Metal Batteries: from Electrode Preparation to Performance Enhancement

AbstractAqueous zinc metal batteries (AZMBs) have emerged as a focal point of interest in academic research and industrial strategic planning. Zinc powder (ZP) is poised to assume a prominent position in both future research and practical applications due to its high Zn utilization rate and processability. However, critical challenges need to be addressed before realizing substantial progress. Notably, severe voltage polarization and gas production of ZP electrodes stand out as the primary causes of battery failure, differing with zinc foil where short circuits caused by zinc dendrites contribute to battery failure. While numerous comprehensive reviews have offered effective strategies for zinc foil, a systematic summary of ZP electrodes is still lacking. For ZP, electrode preparation dictates the performance. This review summarizes the criteria for optimal ZP electrodes, covering electrode components, preparation methods, and technique parameters. It emphatically introduces the underlying causes and strategies of water‐related side reactions and briefly analyzes the stripping/plating behaviors of ZP electrodes. The status quo of ZP‐based batteries is then discussed in categories of ZP, current collector, conductive scaffold, binder, and electrolytes. Finally, potential avenues for future research are proposed from three aspects to enhance the focus on ZP electrodes and facilitate the practical application of AZMBs.