Analysis Of 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.

Risk analysis of lithium-ion battery accidents based on physics-informed data-driven Bayesian networks

The catastrophic consequences of lithium-ion battery (LIB) accidents have attracted high attention from society and industry. Accordingly, risk analysis is indispensable for the risk prevention and control of LIBs. Nevertheless, it is difficult to establish a physics-informed risk analysis model due to the complex material characteristics and aging mechanisms of LIBs. Meanwhile, the data-driven approach requires historical information of LIBs and does not merely rely on knowledge of the internal mechanisms of LIBs. This study proposes a method integrating the physics-informed Bayesian network (BN) (i.e., mapping from fault tree) and data-driven BN (i.e., learning from data) to conduct risk analysis of LIBs. First, we establish physics-informed and data-driven BNs. Subsequently, we bridge physics-informed and data-driven BNs to establish a Bayesian network for risk analysis of LIB accidents. Second, we set up safety barriers in the system, including detectors, emergency response, and firefighting facilities. Third, we evaluate the performance of safety barriers. We validate the proposed model using data from LIBs in air transportation. The results indicate that safety barriers can reduce the accidental risk of LIBs. Eventually, we propose suggestions for the risk control of LIBs in air transportation. This study is supposed to provide theoretical basis for the risk prevention and control of LIB accidents.

Analysis of Lithium-ion Batteries through Electrochemical Impedance Spectroscopy Modeling

Electrochemical impedance spectroscopy (EIS) is a very effective methodology employed in the evaluation of performance and degradation mechanisms associated with lithium-ion batteries. In order to comprehend the complex electrochemical processes taking place within these energy storage devices, reliable and effective diagnostic tools are required due to the constant improvements in battery technology. EIS methodology has gained prominence as a very effective non-destructive method for examining the electrochemical characteristics of batteries. This technique offers significant contributions by providing useful insights into the internal operations of batteries. The main objective of this study is to create an electrical equivalent circuit model of a lithium-ion battery based on physics, and then use EIS to comprehend the electrical behavior and impedance of the battery to evaluate its performance under various operating scenarios. We seek to identify the critical elements influencing the battery’s capacity, performance, and lifespan by capturing the intricate interaction of EIS. The results of this research are going to enhance the understanding of battery behavior and supporting the design as a more reliable and efficient energy storage systems for a wide range of applications, from portable electronic devices to electric vehicles and renewable energy integration.

Correlating phase transition with heat generation through calorimetric data

Despite the widespread utilization of Lithium-ion batteries (LIBs), concerns regarding safety during operation persist owing to accidents and potential risks of fires and explosions. To comprehend the thermal dynamics that underlie severe LIB incidents, calorimetry tests have been prevalently employed for over three decades to examine the exothermic/endothermic behavior, reaction kinetics, and thermal interactions among LIB materials. There exists a substantial volume of calorimetry test results on various LIB electrodes, electrolytes, and other components. However, this data showcases low consistency, yielding an unreliable database that obstructs a thorough understanding of LIB thermal behavior. In this research, a comparative analysis of differential scanning calorimetry (DSC) results from materials utilized in the most commercialized LIB systems is conducted. The analysis unveils notable discrepancies in DSC data amassed by different researchers, identifies five predominant causes of data inconsistency, proposes a standardized DSC operational procedure, and generates a set of self-consistent data. Subsequently, an intrinsic safety spectrum is delineated and compared with X-ray diffraction (XRD) outcomes to elucidate the correlation between the crystal lattice structure and the thermal behavior of the material. This work aids in the formation of a comparative DSC database, utilizing the vast but inconsistent literature data. Moreover, it clarifies the linkage between the material structure and thermal behavior, facilitating data-driven thermal analysis of LIBs.

A voltage reconstruction model for lithium-ion batteries considering the polarization process

Health assessment is one of the most crucial components in lithium-ion battery (LIB) management. However, traditional methods often require disassembling LIBs, which are inconvenient for implementation. On the contrary, non-destructive diagnostics can obtain the aging information of LIBs without causing damage to batteries, which is beneficial for the periodic inspection and secondary use of LIBs in other fields. Therefore, accurate non-destructive diagnostics is necessary in practical applications. This paper proposes a new voltage reconstruction model considering the polarization process to get the battery internal information. Through matching the equilibrium potentials of the positive and negative electrodes, combined with an equivalent circuit model, this voltage reconstruction model can accurately simulate the whole charging and discharging processes of LIBs. The parameters with clear physical interpretation in the model can be quickly and accurately identified within the MATLAB software, and these parameters can be used to quantitatively identify the degradation modes of LIBs. Finally, the post-mortem analysis of the aged LIB is used for verification. The results show that the proposed model could precisely reflect the battery internal ageing information and could be used for online diagnostics in real electric vehicles.

Utilizing Bayesian Optimization to Facilitate Differential Voltage Analysis of Lithium Ion Batteries

Differential voltage analysis (DVA) is a non-destructive, in situ method for analyzing degradation in lithium ion (Li-ion) batteries, and can be used to identify major modes of performance degradation, such as loss of lithium inventory (LLI) and loss of active material (LAM). Using the cycling voltage derivative with respect to capacity of half cells and full cells, DVA can be used to estimate which mode is the main contributor to degradation. Analysis of the signature peaks in the half cell to the full cell can reveal the degradation mode of full cell. Shifts in the peak can indicate LLI, while intensification and narrowing of peaks can indicate LAM. Analyzing the peak changes after cycling allows quantitative determination of how much cell aging has occurred, and what mode is involved in the cell aging process. However, the process of analyzing peak changes manually is inefficient and time consuming. In this work, we utilize a Bayesian optimization approach to facilitate the process of fitting full cell DVA data with pristine half-cell data. The Bayesian optimization algorithm finds the best deformation of pristine half-cell data to fit full-cell data automatically and efficiently for multiple chemistries. The only manual procedures for each fitting are reading data files into the program and determining a coarse bound. The rest is automated and takes less than ten minutes for each fitting. The fitting accuracy is comparable to manual fitting and significantly less time consuming. This method facilitates battery aging analysis and can be generalized to different kinds of data sets as well.

Experimental studies of reciprocating liquid immersion cooling for 18650 lithium-ion battery under fast charging conditions

In this study, the reciprocating liquid immersion cooling has been proposed and tested for cooling the cylindrical lithium-ion battery (LIB) under fast charging conditions. First, the temperature responses of LIB under fast charging conditions with liquid immersion cooling and natural convection are compared. Experimental results show that the reciprocating liquid immersion cooling possesses better heat dissipation performance than natural convection, not only can precisely control the cell temperature to around 50 °C during fast charging, but also can improve the cell temperature uniformity. Meanwhile, the reciprocating system enables rapid cooling of the battery during the resting process, which consequently achieves asymmetric control of high-temperature charging and room temperature discharging. Then, the effects of different charging rates and different charging protocols are explored, and the high-speed photography is used to observe and record the liquid-gas phase transition phenomenon under three different charging rates. Finally, the temperature response and energy consumption analysis of LIB in the fast-charging process with three different assembly schemes are investigated. This study provides preliminary proof for the advantage of applying liquid immersion cooling for LIB under fast charging.

Investigation on step overcharge to self-heating behavior and mechanism analysis of lithium ion batteries

To obtain intrinsic overcharge boundary and investigate overcharge mechanism, here we propose an innovative method, the step overcharge test, to reduce the thermal crossover and distinguish the overcharge thermal behavior, including 5% state of charge (SOC) with small current overcharge and resting until the temperature equilibrium under adiabatic conditions. The intrinsic thermal response and the self-excitation behaviour are analysed through temperature and voltage changes during the step overcharge period. Experimental results show that the deintercalated state of the cathode is highly correlated to self-heating parasitic reactions. Before reaching the upper limit of Negative/Positive (N/P) ratio, the temperature changes little, the heat generation is significantly induced by the reversible heat (endothermic) and ohmic heat, which could balance each other. Following that the lithium metal is gradually deposited on the surface of the anode and reacts with electrolyte upon overcharge, inducing self-heating side reaction. However, this spontaneous thermal reaction could be “self-extinguished”. When the lithium in cathode is completely deintercalated, the boundary point of overcharge is about 4.7 V (∼148% SOC, >40 °C), and from this point, the self-heating behaviour could be continuously triggered until thermal runaway (TR) without additional overcharge. The whole static and spontaneous process lasts for 115 h and the side reaction heat is beyond 320,000 J. The continuous self-excitation behavior inside the battery is attributed to the interaction between the highly oxidized cathode and the solvent, which leads to the dissolution of metal ions. The dissolved metal ions destroy the SEI (solid electrolyte interphase) film on the surface of the deposited Li of anode, which induces the thermal reaction between lithium metal and the solvent. The interaction between cathode, the deposited Li of anode, and solvent promotes the temperature of the battery to rise slowly. When the temperature of the battery reaches more than 60 °C, the reaction between lithium metal and solvent is accelerated. After the temperature rises rapidly to the melting point of the separator, it triggers the thermal runaway of the battery due to the short circuit of the battery.

Optimising the geospatial configuration of a future lithium ion battery recycling industry in the transition to electric vehicles and a circular economy

Rapid electrification of the transport system will generate substantial volumes of Lithium-ion-battery (LiB) waste as batteries reach their end-of-life. Much attention focuses on the recycling processes, neglecting a broader systemic view that considers the concentration of the costs and impacts associated with logistics and transportation. This paper provides an economic, environmental and geospatial analysis of a future LiB recycling industry in the UK. Hitherto, state-of-the-art assessment methods have evaluated life cycle impacts and costs but have not considered the geographical layer of the problem. This paper develops a GSC derived supply chain model for the UK electric vehicle and end-of-life vehicle battery industry. Considering both pyrometallurgical and hydrometallurgical recycling technologies, the optimisation process takes into account anticipated EV volumes, and, based on anticipated near-term technological evolution of LiBs, the evolution of the mix of battery cathodes in production, and presents a number of scenarios to show where LiB recycling facilities should ideally be geographically located. An economic and environmental assessment based on a customised EverBatt model is provided.

Quantifying lithium lost to plating and formation of the solid-electrolyte interphase in graphite and commercial battery components

A key degradation mechanism in lithium-ion batteries (LIBs) is the irreversible loss of cyclable lithium during cycling. At the graphite negative electrode, this loss occurs through the deposition of lithium-containing compounds in the solid-electrolyte interphase (SEI) and through plating of metallic lithium, resulting in so-called dead lithium. The separate quantification of SEI and dead lithium has so far been a challenge in post mortem analysis of commercial LIBs. Here we report a simple and fast 7Li nuclear magnetic resonance spectroscopy (NMR) protocol applied to solid-state samples derived from lab-built batteries to independently quantify these and other lithium species in graphite electrodes without the need for specialized cell design nor knowledge of prior charging history. The metallic lithium content is corroborated by electrochemical calculations; the total amount of lithium is also determined from 7Li liquid-state NMR and inductively coupled plasma optical emission spectroscopy (ICP-OES) in suitably digested samples. Factors influencing accuracy like the sample handling process, the radiofrequency skin effect, and re-intercalation losses are investigated. Measurements on samples from commercial cells aged under realistic conditions demonstrate quantification of dead lithium and remaining ionic species (SEI), and further reveal lithium dendrites entrained in the separator following cell disassembly. The method uses conventional and widely available NMR instrumentation and is applicable to samples from lab-scale test cells or commercial batteries, thereby presenting a vast improvement over prior post mortem methods.

Analysis of Lithium-Ion Battery through Direct Current Internal Resistance Characteristic

Analysis of Lithium-Ion Battery through Direct Current Internal Resistance Characteristic

Thermal Management and Exergo-Economic Analysis of Lithium-Ion Batteries Using Force Convection of Water- Nano Encapsulated Phase Change Materials (NEPCMs) Nanofluids

Thermal Management and Exergo-Economic Analysis of Lithium-Ion Batteries Using Force Convection of Water- Nano Encapsulated Phase Change Materials (NEPCMs) Nanofluids

Degradation Modes and Mechanisms Analysis of Lithium-Ion Batteries with Knee Points

Degradation Modes and Mechanisms Analysis of Lithium-Ion Batteries with Knee Points

The Anisotropic Homogenized Model for Pouch Type Lithium-Ion Battery Under Various Abuse Loadings

Abstract Pouch type lithium-ion battery (LIB) has now been widely used in electric vehicles, smartphones, and computers. Mechanical abuse is one of the main reasons to cause the safety issues for lithium-ion battery. The highly accurate and efficient computational model is helpful for the safety design, application, and analysis of LIB. The previous homogenized mechanical models of the pouch LIB use different material parameters for various loading conditions. Herein, we establish an anisotropic homogenized method to predict the mechanical behavior in in-plane and out-of-plane directions simultaneously. Engineering constants and Hill's 48 criteria are used for the anisotropic properties, and bilinear plastic model is used as the hardening curve under large deformation. On the basis of this method, we established two homogenized models, i.e., one-layer model and multilayer model. Experiments in various loading conditions including three-point bending (length direction and width direction), out-of-plane compression, and in-plane compression (length direction and width direction) are conducted for parameters calibration. The calibration methods are then discussed and confirmed through these experiments. The computational models show good correlation with experiments in both in-plane and out-of-plane directions. The difference is that the global buckling behavior can be predicted by both of the two models, while the local buckling can be predicted only by the multilayer model. The results may shield light on the safety design, application, and analysis for pouch LIB.

Sustainable and Low-Cost Lithium-Ion Batteries: Nonconventional Electrode Chemistries and State of Health Characterization

With the advancements in portable electronics and electric vehicle (EV) applications, the demand for lithium-ion batteries (LIBs) with high energy densities is ever increasing. Battery-powered transportation is being adopted more frequently due to its potential to enable a more sustainable society by reducing vehicle emissions from fossil fuels. There has been exponential growth in the need for high-capacity LIBs in all types of EVs, including hybrid and full electric automobiles, e-bikes, and drones, as well as electric tools, cell phones, tablets, and, more recently, house storage; this growth significantly increases the consumption of source material commodities, especially cobalt. Despite its drop in price in the last couple of years due to increased mining, cobalt remains expensive, and its price increase has gained momentum again compared to other electrode materials due to higher demand. Moreover, its toxicity and difficult mining practices could result in many problems, including excessive carbon dioxide and nitrogen dioxide emission along with a possible much higher demand in the long term. This provides a strong motivation to explore alternatives to battery source materials. In this article, we present a selection of our important works on LIBs, with a focus on alternative electrode chemistries by using abundant and sustainable material sources. As alternatives to traditional graphite-based anodes, we demonstrate the successful use of both silicon electrodes derived from beach sand and waste glass and carbon electrodes derived from portobello mushroom and waste plastic precursors. In addition, we demonstrate stable cycling of batteries with nonconventional electrode chemistries, such as lithium-sulfur with TiO2-coated sulfur electrodes and sulfur-silicon full cell batteries with integrated lithium sources. Batteries prepared by sustainable methods not only perform better than conventional ones but also result in reduced costs. Since accurate determination of battery state of health is another important challenge, we further present our electrochemical impedance spectroscopy-based analysis of LIBs, which could potentially be utilized in safety evaluations of current and next-generation LIBs.

Efficient Direct Recycling of Lithium-Ion Battery Cathodes by Targeted Healing

<h2>Summary</h2> Recycling of spent lithium-ion batteries (LIBs) is an urgent need to address their environmental and global sustainability issues. Here, we report an efficient and environmentally benign LIB regeneration method based on defect-targeted healing, which represents a paradigm-shift LIB recycling strategy. Specifically, by combining low-temperature aqueous solution relithiation and rapid post-annealing, we demonstrate successful direct regeneration of spent LiFePO₄ (LFP) cathodes, one of the most important materials for EVs and grid storage applications. We show revitalization of composition, structure, and electrochemical performance of LFP with various degradation conditions to the same levels as the pristine LFP. Life-cycle analysis of different LIB recycling processes shows that this defect-targeted direct reycling approach can significantly reduce energy usage and greenhouse gas (GHG) emissions, leading to more economic and environmental benefits compared with today's hydrometallurgical and pyrometallurgical methods.

Economic analysis of lithium-ion batteries recycled from electric vehicles for secondary use in power load peak shaving in China

The secondary use of recycled lithium-ion batteries (LIBs) from electric vehicles (EVs) can reduce costs and improve energy utilization rate. In this paper, the recycled LIBs are reused to construct a 3 MW∗3 h battery energy storage system (BESS) for power load peak shaving (PLPS). Taking the BESS as an example, a cost-benefit model is established after the systematical analysis of compositions. The cost model is divided into eight components in detail, which can be grouped into three categories: initial investment costs, operation and maintenance costs (O&M costs) and batteries replacement costs. The benefit model comprises seven parts, such as environmental benefit, battery dismantling and recovery benefit and residual value. In the case study, the life model is established by exponential function through the character analysis of the recycled LIBs. The economic analysis of the BESS is carried out in three techno-economic statuses of optimism, business, and research, which is based on two interest-subjects of grid company and non-grid company. Furthermore, both battery purchasing cost (BPC) and government subsidy are performed to sensitivity analysis. The results show that the BESS with recycled LIBs for PLPS, especially those invested by grid company, have a good application prospect in China.

Failure mode analysis of lithium ion batteries operated for low Earth orbit CubeSat applications

Abstract Three types of 18-65 cylindrical lithium-ion cells with different positive active materials (NCA – nickel cobalt aluminium, NMC – nickel manganese cobalt, LFP – lithium iron phosphate), negative active material graphite average particle sizes (2 – 30 µm) and electrode designs (high power, high energy) were tested using an accelerated low earth orbit (LEO) CubeSat power profile cycle. Each design yields a unique energy density, power capability and cycle life. Each cell type was tested in a 3P group configuration at 10°C in atmospheric pressure (101 kPa-abs) and under vacuum (0.2 kPa-abs). Cell groups were operated in their respective pressure condition until they failed to successfully execute the accelerated LEO cycle. In atmospheric pressure and vacuum, both NMC groups failed due to internal resistance (IR) growth. The atmospheric pressure NCA group failed due to excessive internal gas build-up triggering the current interrupt device (CID) to electrically disconnect. The NCA group in vacuum failed from both IR growth and capacity degradation. The LFP groups both in atmospheric pressure and vacuum have completed approximately 5078 LEO cycles or 2800 equivalent cycles of initial measured coulombic capacity and are still operational with 19% and 21% capacity degradation from their initial measured coulombic capacity, respectively.

Mechanical analysis and design of flexible beads-and-thread lithium-ion battery

Novel beads-and-thread structural designs have been applied in the new-generation flexible lithium-ion batteries (LIBs) to achieve high electrochemical performance and high flexibility simultaneously. However, to understand the mechanical degradation and to obtain the best performance of these flexible LIBs, the structural analysis and design of such LIBs are of crucial importance. Accordingly, it is necessary to establish detailed and systematic analytic and simulation models to describe the mechanical behavior of these LIBs. Here, the flexibility, energy density, and safety criterion of beads-and-thread LIBs are quantitatively discussed by an analytic finite deformation model and a finite element analysis (FEA) model. The trade-off between effective flexibility and relative energy density of LIBs has been discussed with the parametrical study of two key geometric parameters, length ratio and winding layer number of the structural element. Stress/strain analysis reveals the yield of the Al foil layer in unwound part could be a safe criterion for evaluating mechanical degradation of the battery. Rational design diagrams of flexibility and relative energy density are investigated for the battery designers, considering the balance of battery safety, mechanical and energy storage properties. This work is expected to provide the design guidelines for flexible beads-and-thread LIBs.

From the Perspective of Battery Production: Energy–Environment–Economy (3E) Analysis of Lithium-Ion Batteries in China

With the wide use of lithium-ion batteries (LIBs), battery production has caused many problems, such as energy consumption and pollutant emissions. Although the life-cycle impacts of LIBs have been analyzed worldwide, the production phase has not been separately studied yet, especially in China. Therefore, this research focuses on the impacts of battery production and builds an energy–environment–economy (3E) evaluation system. Two battery factories in China were selected for an applied research. Case 1 annually produces 0.22 GWh lithium iron phosphate (LFP) batteries, while case 2 produces 0.024 GWh lithium nickel manganese cobalt oxide (NCM) batteries. The results demonstrate that electricity consumption per GWh LIBs production is 5.24 × 104 and 4.13 × 104 kWh for case 1 and 2, respectively. Major water pollutant emissions come from employees’ lives, and domestic waste accounts for 82%–83% of the total waste. Material costs per GWh NCM battery are 2.77 × 105 yuan, which is more expensive than the LFP battery, whose cathode material is relatively cheaper. Moreover, the cradle-to-gate carbon footprints (CFs) of the GWh LIBs are 41392.17 and 32254.57 kg CO2eq. The lithium compounds are major contributors to carbon emission for two LIBs. Some measures such as cleaner production, scale expansion and increase of environmental protection investment can effectively promote the development of a 3E system for LIB factories.