Lithium Battery Production Research Articles

Study on chloride attack resistance of concrete with lithium slag content

The demand for lithium batteries in electronic products is constantly increasing, and a large amount of solid waste is generated during the production of lithium batteries. These wastes are not only harmful to the environment, but more importantly, the cost of processing the wastes is very high. To reduce the harm caused by lithium slag waste and increase the chloride ion penetration resistance of concrete, this paper designs C20, C30, C40, and C60 concrete with lithium slag contents of 0 %, 10 %, 20 %, and 30 %. The effects of different lithium slag contents on the compressive strength, electric flux, and porosity of concrete specimens were studied. The study found that for C20, C40, and C60 concrete, the compressive strength decreases with the increase of lithium slag content. For C30 concrete, the compressive strength shows a trend of increasing first and then decreasing with the increase of lithium slag content. For the electric flux of C20, C30, and C40 concrete, it shows a trend of decreasing with the increase of lithium slag content. For the porosity of C20, C30, and C40 concrete, it shows a trend of first decreasing and then increasing with the increase of lithium slag content. Combining Fick's second law and the law of conservation of mass, a chloride ion penetration model of lithium slag concrete under the action of different lithium slag contents was established. The results show that the penetration performance of chloride ions in the immersion environment conforms to the experimental law; the maximum error between the simulation results and the test results is at 360 min of C30-30LS, and the error value is 14.49 %.

Numerical Study on the Coating Uniformity of Slot-Die Head Using FSI Method

Abstract Slot-die coating technology is one of the key processes in the production of lithium batteries. The design of die head, which is the core component of slot-die coating system, affects quality of lithium batteries directly. In this paper, Fluid-Structure Interaction (FSI) method is employed to evaluate the influence of die head deformation on coating quality. The results demonstrate that the FSI method provides a more accurate assessment of the influence of die head deformation on coating quality parameters compared to conventional methods. Based on this method, a reasonable range of operating pressure is determined for a specific model of coating head.

An improved ensemble learning model-based strategy for fault diagnosis of lithium battery double roller press equipment

Abstract The production process of lithium batteries is intricate, involving the coordination of various types of equipment.The sta-bility and precision of double roller press equipment directly affect product performance. With the increasing global de-mand for green energy, the application of lithium batteries in electric vehicles and energy storage systems is expanding, which imposes higher requirements on the stability and quality of lithium battery production. It is an important topic to address the challenges brought about by the gradual intelligentization of double roller presses, such as the complexifica-tion of control systems and the diversification of fault reasons. This paper proposes an enhanced ensemble learning model-based fault diagnosis strategy for lithium battery double roller press equipment. Firstly, the K-nearest neighbors (KNN) algorithm is employed to handle missing data, combined with normalization and standardization methods to improve fea-ture processing, thereby enhancing data quality. Secondly, the Maximum Information Coefficient (MIC) algorithm is utilized to select features highly correlated with fault labels, combined with the Recursive Feature Elimination with Cross-Validation (RFECV) to further optimize feature selection, creating an optimal feature subset. Finally, a RXS-XGBoost model is constructed through the Stacking ensemble learning method, selecting Random Forest (RF), XGBoost, and Sup-port Vector Machines (SVM) as base learners, with XGBoost as the meta-learner. This ensemble approach aims to lever-age the complementary advantages of different algorithms, enhancing the accuracy and robustness of fault diagnosis. The experimental results demonstrate that this improved ensemble learning diagnostic strategy achieves an accuracy rate of up to 99.05%, which is significantly better than other fault diagnosis strategies. It not only effectively reduces the model's training complexity and the risk of overfitting but also significantly enhances the efficiency and precision of fault diagno-sis for lithium battery double roller press equipment.

Fluid–Solid Mixing Transfer Mechanism and Flow Patterns of the Double-Layered Impeller Stirring Tank by the CFD-DEM Method

The optimization design of the double-layered material tank is essential to improve the material mixing efficiency and quality in chemical engineering and lithium battery production. The draft tube structure and double-layered impellers affect the flow patterns of the fluid–solid transfer process, and its flow pattern recognition faces significant challenges. This paper presents a fluid–solid mixing transfer modeling method using the CFD-DEM coupling solution method to analyze flow pattern evolution regularities. A porous-based interphase coupling technology solved the interphase force and could be used to acquire accurate particle motion trajectories. The effect mechanism of fluid–solid transfer courses in the double-layered mixing tank with a draft tube can be obtained by analyzing key features, including velocity distribution, circulation flows, power, and particle characteristics. The research results illustrate that the draft tube structure creates two major circulations in the mixing transfer process and changes particle and vortex flow patterns. The circulating motion of the double-layered impellers strengthens the overall fluid circulation, enhances the overall mixing efficiency of the fluid medium, and reduces particle deposition. Numerical results can offer technical guidance for the chemical extraction course and lithium battery slurry mixing.

Study on the Adsorption of Trace Water in N-Methyl-pyrrolidone Solvents by A-Type Molecular Sieves.

N-Methyl-pyrrolidone (NMP) is an important coating solvent for the production of lithium batteries, and its water content will greatly affect the coating quality and energy density of lithium batteries, which needs to be reduced to 200 ppm. The current vacuum distillation technology suffers from high operating costs and high energy consumption, whereas the pervaporation technology only achieves solvent dehydration up to 99.5%. Therefore, it is of great significance to carry out the study of trace water removal from NMP solvents. In this paper, the A-type molecular sieve adsorption method was used to remove trace water from the NMP solvent, and the effects of molecular sieve type, particle size, adsorption temperature, feeding amount, and contact time on the dehydration performance of NMP system were first investigated. Adsorbed at 25 °C for 240 min at a feeding amount of 120 g/L, 3A molecular sieves were able to reduce the water content of the NMP solvent from 5000 to 140 ppm. Second, Langmuir and Freundlich equations were used to fit the static isothermal adsorption data, and the results showed a better correlation of the Langmuir equation. Then, the adsorption kinetics and diffusion mechanism were analyzed by the kinetic model and the Crank single-pore diffusion model. The R2 of the pseudo-first-order kinetic model was 0.9993, which was more suitable for describing the process of adsorption of water from the NMP solvent by 3A molecular sieves, and the effective diffusion coefficient De = 2.986 × 10-8 cm2/s was calculated for the Crank single-pore adsorption model, which proved water molecules on the 3A molecular sieve. The diffusion of water molecules on the inner surface of the pores is the controlling step of the adsorption process. Finally, the fixed-bed dynamic penetration curves were investigated to obtain the experimental data of fixed-bed adsorption, and the experimental data were fitted using the Thomas and Yoon-Nelson models, which showed that both models could describe the adsorption behavior of trace water in NMP solvents on 3A molecular sieves. This study provides a new idea for the removal of trace water in NMP systems, and a series of model fitting parameters provide basic data for industrial scale-up.

Study of water-side free cooling technology for power lithium battery plant

Power lithium battery production process needs to consume a lot of energy. In this paper, an energy consumption analysis of a representative company was conducted, the energy consumption of the facilities that provide support for the process is higher than the energy consumption of the process equipment itself, which greatly affects the cost of battery manufacturing. Air-conditioning system as the most important energy-consuming system of the facilities, accounting for 25% to 45% of the total electricity consumption. The energy consumption of the cooling source system dominates, even in winter its energy consumption can reach 14% of the total energy consumption. On this basis, this paper analyzes the chilled-water-use characteristics of the air-conditioning terminal in winter through theoretical analysis, the chilled water temperature is therefore optimized according to the real-time outdoor humidity. The chilled water temperature is linearly increased after the humidity ratio fall below 7.5g/kg(a), reaching a maximum value of 12.1°C at 6g/kg(a). In addition, the cooling tower free cooling technology based on the optimized chilled water temperature is innovatively proposed to fully explore the energy-saving potential of the technology to achieve the energy saving of the cooling source system. TRNSYS simulation results show that after optimizing the chilled water temperature, the time period for cooling tower individual cooling under winter operating condition is extended by 60%, and cooling source system energy saving rate can reach 49.0% and the cost saving rate 48.0%, both of which are higher than 15% compared to the un-optimized chilled water temperature.

Improvement of lithium battery corner detection accuracy based on image restoration method

Target detection technology has been widely used in the automatic production of lithium batteries. However, motion blur will lead to the reduction of the angular position detection accuracy of lithium batteries. To solve this problem, an improved fuzzy recovery model for angular position of lithium battery is proposed in this paper. Firstly, the improved lightweight neural network RepVGG was used as the main module of the backbone network, so that the network could improve the performance of network feature extraction while reducing the number of calculation parameters and improving the reasoning speed of fuzzy restoration. Secondly, we optimize the multi-Dconv head transposed attention (MDTA) module and reference it to the generator, which reduces the complexity of the model and strengthens the network’s attention to details and textures, and improves the visual effect of the restored image. Finally, we design a lightweight globally connectable residual network called SAC Block and use it to to improve the discriminator, which enhances the global receptive field of the model and improves the structural similarity between the restored image and the original image. In order to verify the effectiveness of the method, we verify it on the self-built dataset and GoPro dataset. The experiments show that our proposed lightweight model improves the peak signal-to-noise ratio (PSNR) index by 9.2% and 8.6% respectively compared with the original model. The visual effect of the restored image is better than that of other current similar algorithms, and it is confirmed that our model can better improve the accuracy of lithium battery angular position detection.

Prediction of Lithium Oilfield Brines Based on Seismic Data: A Case Study from L Area, Northeastern Sichuan Basin, China

Lithium is an important mineral resource and a critical element in the production of lithium batteries, which are currently in high demand. Oilfield brine has significant value as a raw material for lithium extraction. However, it is often considered a byproduct of oil and gas production and is either abandoned or reinjected underground. Exploration and development of oilfield brines can enhance the economic benefits of oilfields and avoid wasting resources. Current methods for predicting brine distribution rely on geological genetic analysis, which results in low accuracy and reliability. To address this issue, we propose a workflow for lithium brine prediction that uses seismic and logging data. We introduced waveform clustering control and used the mapping relationship between seismic waveforms and well-logging curves to predict high-quality reservoirs based on the electrical and physical properties of lithium brine reservoirs. In this workflow, the seismic waveforms were first clustered using singular value decomposition. The sample sets of well-logging properties were established for the target location. The target properties were divided into high- and low-frequency components and predicted separately. The predicted results of the high-quality reservoirs in the study area were verified using elemental content test results to demonstrate the effectiveness of the method. Our study indicates that well-logging property prediction constrained by waveform clustering can predict lithium brines in a carbonate reservoir.

BENEFITS OF LITHIUM MINING TO NIGERIA’S ECONOMIC DEVELOPMENT

Lithium mining goes beyond the extraction of lithium ore; it involves the technological importance of the mineral together with its application. This refers to eco-friendly applications such as the production of electric cars, the production of lithium batteries for solar panels, and other electrical devices. Obtained lithium (spodumene) samples from visited mine sites in Gidan Kwano (Nasarawa State), Kokona (Nasarawa State), and Takushara (Abuja-Kuje LGA) were taken to the laboratory for analysis. The atomic absorption spectrometry result shows a lithium percentage that ranges from 1% to 4.5% (low to high grade). A statistical analysis of data for total production of lithium in a month (through interactive sessions with miners on-site) shows that over 20 tons of lithium can be produced in a month by an active lithium mine site. Conclusively, if 20 tons is used as the benchmark, this means that a total of 40 trucks worth ₦20,375,000,000 will be made per month and a total of ₦244,500,000,000 per year. With this amount of money, after the removal of various royalties, it can go a long way in handling various issues in the state, local government, and even at the federal level. Well-monitored lithium mining can create jobs for indigenous people in the community, and the financial contribution can increase the internally generated revenue. The production of electric cars in Nigeria will also help solve the issue of carbon emissions and create a friendly eco-system.

A real-time method for detecting bottom defects of lithium batteries based on an improved YOLOv5 model

Defect detection of lithium batteries is a crucial step in lithium battery production. However, traditional detection methods mainly rely on the human eyes to observe the bottom defects of lithium battery products, which have low detection accuracy and slow detection speed. To solve this practical problem, an improved YOLOv5s model is proposed in this paper. Firstly, a new layer of the network output layer is added to improve the detection effect of small defects. Secondly, to extract important information in the feature maps, the convolutional block attention module attention mechanism is added to the YOLOv5s model. Finally, a new position loss function is used to improve the accuracy of the position prediction of the model. The experimental results indicate that the improved YOLOv5s model can accurately and quickly detect three types of defects on the bottom surface of lithium batteries. Specifically, the loss and mean average precision (mAP) of the improved YOLOv5s model are 0.033 94 and 67.5% respectively. Compared with the traditional YOLOv5s model, the loss of the improved YOLOv5s model is reduced by 31%. As well as, the mAP of the improved YOLOv5s model is increased by 4.3% on the lithium battery defect dataset. Compared with the YOLOv3, YOLOv3-spp, retinanet and YOLOv4, the mAP of the improved YOLOv5s model increased by 5.4%, 0.7%, 11.9% and 3.7% respectively. Compared with other improved YOLOv5 algorithms used in various fields, the mAP of the proposed model on the lithium battery dataset is the highest. The detection speed of the improved YOLOv5s model reaches 111 frames per second, which can meet the real-time detection requirements. The improved YOLOv5s model has board application prospects in the industrial production of lithium batteries.

A novel approach for surface defect detection of lithium battery based on improved K-nearest neighbor and Euclidean clustering segmentation

Surface defects of lithium batteries seriously affect the product quality and may lead to safety risks. In order to accurately identify the surface defects of lithium battery, a novel defect detection approach is proposed based on improved K-nearest neighbor (KNN) and Euclidean clustering segmentation. Firstly, an improved voxel density strategy for KNN is proposed to speed up the effect for point filtering. Then, the improved clustering segmentation strategy is applied to distinguish point clouds with defect features. The outline fitting algorithm based on the least square method is applied to determine geometric features of each surface defect which are used to classify defect types. Furthermore, experimental results show that the proposed surface defect detection method reaches 99.2% accuracy and 35.3-ms average time consumption for data processing. Finally, an industrial application example of lithium battery production is demonstrated, which meets the requirements of industrial application. All these reports exhibited that the industrial visual inspection system with rapid measurement is an effective method and guarantees for accelerating industrial production and manufacturing in the future.

A Protophilic MOF Enables Ni-Rich Lithium-Battery Stable Cycling in a High Water/Acid Content.

Trace protic impurities, such as water and hydrofluoric acid (HF), can severely degrade the stable and long cycling of lithium batteries. Therefore, the costly water removal process is inevitably needed throughout production of lithium batteries, leaving the paradox that energy-saving lithium-battery technology consumes non-negligible amounts of energy. Herein, a unique ionic metal-organic framework (MOF) is reported that enables highly destructive H2 O/HF-tolerant lithium batteries. The isolated ionic fluorine sites in the MOF exhibit unusual protophilicity and efficiently capture ppm-levels H2 O/HF from the highly polar electrolyte solvents. The resulting MOF-based LiNi0.6 Mn0.2 Co0.2 O2 │Li battery achieves over 300 cycles in the presence of 800ppm H2 O or 1107ppm acidic impurity. This tenfold longer battery lifespan relative to those for batteries with conventional standard separators demonstrates its excellent electrochemical cycling performance. The results reveal that the rational use of unique nanoporous features of MOFs can provide new possibilities for long-standing challenges in the lithium-battery industry.

Separation of Valuable Metals in The Recycling of Lithium Batteries via Solvent Extraction

With the development trend and technological progress of lithium batteries, the battery market is booming, which means that the consumption demand for lithium batteries has increased significantly, and, therefore, a large number of discarded lithium batteries will be generated accordingly. Solvent extraction is a promising approach because it is simple. Solvent extraction is low in time consumption and is easy to industrialize. This paper is focused on the selective recovery of cobalt (Co), nickel (Ni), and manganese (Mn) contained in leachate obtained by digesting a cathodic material from spent lithium batteries with hydrochloric acid. After leaching the cathodic material, Mn was selectively extracted from leachate by using solvent extraction with D2EHPA diluted in kerosene in an optimized condition. Afterward, Co was extracted from the Mn-depleted aqueous phase using Cyanex272 diluted in kerosene. Finally, the raffinate obtained via a stripping reaction with H2SO4 was used in the Ni extraction experiments. Cyanex272 extractant was employed to separate Ni and Li. The process can recover more than 93% of Mn, 90% of Co, and 90% of Ni. The crucial material recovered in the form of sulfuric acid solutions can be purified and returned to the manufacturer for use. This process proposes a complete recycling method by effectively recovering Mn, Co, and Ni with solvent extraction, to contribute to the supply of raw materials and to reduce tensions related to mineral resources for the production of lithium batteries.

Comminution and Classification as Important Process Steps for the Circular Production of Lithium Batteries

Lithium-ion batteries (LIBs) provide the largest source of electrical energy storage today. This paper covers the use of comminution processes and, thus, crushers and mills for particle breakage and dispersing, as well as classifiers for particle separation within the process chain, from the raw material to the final lithium battery cell and its recycling at end of life. First of all, the raw materials for the active material production have to be produced either by processing primary raw materials, or by recycling the spent lithium batteries. The end-of-life battery cells have to be shredded, the materials separated and then milled in order to achieve the so-called black mass, which provides a secondary material source with very valuable components. Using these materials for the synthesis of the cathode active materials, milling has to be applied in different stages. The natural graphite, increasingly used as anode material, has to be designed in mills and classifiers for achieving targeted properties. Nanosized silicon is produced by nanomilling using stirred media mills as a primary option. Conductive additives for LIBs, like carbon black, have to be dispersed in a solvent with machines like planetary mixers, extruders or stirred media mills. In the future, mechanochemical synthesis of solid electrolytes will especially require additional application of comminution processes.

Sim-YOLOv5s: A method for detecting defects on the end face of lithium battery steel shells

The detection of lithium battery shell defects is an important aspect of lithium battery production. The presence of pits, R-angle injuries, hard printing, and other defects on the end face of lithium battery shells severely affects the production safety and usage safety of lithium battery products. In this study, we propose an effective defect-detection model, called Sim-YOLOv5s, for lithium battery steel shells. In this model, we propose a fast spatial pooling pyramid structure, SimSPPF, to speed up the model and embed the attention mechanism convolutional block attention module in the backbone. Contextual information can be aggregated over a large perceptual field by using the new upsampling operator, which has a larger field of perception. A cross-layer connection operation is performed to fuse shallow feature information with deep feature information. The experimental results show that the proposed Sim-YOLOv5s model has a better overall performance with a mean average precision of 88.3%, which is 6.9% better than that of YOLOv5s. Therefore, the proposed Sim-YOLOv5s can lay the foundation for the industrial implementation of real-time inspection of lithium battery products.

Increasing Australian Lithium Production to Meet Electric Vehicles and Net Zero Global Targets: A Decarbonisation Tax Discount?*

Current commitments with net zero 2050 require that more than two billion electric vehicles (EVs) be produced globally by 2035. Australia produces more than 55% of the global lithium in the world. We argue that Australia's most significant contribution to realising net zero 2050 could be to increase lithium production 10‐20‐fold by 2035. A similar case could equally be made for increasing other critical minerals. This would also contribute to securing Australia's energy and national security. To realise these benefits current investment in lithium is much lower than the production of lithium batteries used in EVs requires, reflecting suboptimal tax rates. We conclude by proposing that a decarbonisation tax discount for critical minerals is needed.

Simulation analysis and research of cylindrical lithium battery pack automation equipment system

The performance difference of the single battery has a significant impact on the cruising range, service life, charge and discharge control of an electric vehicle that uses multiple batteries as the power battery. Highly consistent performance is an essential process for lithium battery production. In order to verify the performance of the lithium battery automatic pack system, this paper used Flexsim software to establish a system simulation model, used the Dashboard data statistical method to analyze the running data of the simulation model, completed the system construction and testing, and used SPSS statistical analysis software to analyze the system test results. Using the paired sample T test, we verify that the system matching test results are accurate, that the cylindrical lithium battery matching automation equipment system has complete functions, is simple to interact with the computer, and meets the system design requirements.

A novel air-conditioning system with cascading desiccant wheel and liquid desiccant dehumidifier for low-humidity industrial environments

Numerous industrial workshops require low-humidity environments, including lithium battery production, chip fabrication, some pharmaceutical manufacturing, etc. The desiccant wheel system is the conventional air-conditioning system for maintaining the low-humidity environments. However, only high-humidity outdoor air can be used for desiccant regeneration in some mechanical workshops requiring no mechanical ventilation, which leads to a high regeneration temperature and a poor system energy performance. To enhance the performance, a novel air-conditioning system with cascading desiccant wheel and liquid desiccant dehumidifier for low-humidity industrial workshops is proposed in this study. Solid desiccant and liquid desiccant are innovatively integrated in the proposed system for achieving a supply air dew point temperature below −10 °C. When dehumidifying process air from 5 to 1 g/kg in the basic case, the proposed system shows a competitive COP of 1.6. Under weather conditions in Guangzhou, subtropical China, the proposed system consumes 19.6 % and 58.0 % lower electricity during the summer, compared to the integrated system using outdoor air for regeneration and the desiccant wheel based system, respectively. The proposed system particularly applies to low-humidity industrial workshops in tropical and subtropical regions in summer, where there is a huge air humidity difference between indoors and outdoors. It is anticipated that this study could provide reference for energy saving and carbon emission reduction in low-humidity industrial production process.

Recent Advances in Stability Issues of Inorganic Solid Electrolytes and Composite Solid Electrolytes for All-Solid-State Batteries.

The development of solid-state batteries has become one of the most promising directions in rechargeable secondary batteries due to their considerable energy densities and favorable safety. However, solid-state batteries with higher energy density and more durable and stable cycle life should be developed for large-scale energy storage and adaption to the rapidly increasing lithium battery production and sales market. Although inorganic solid electrolytes (ISEs) and composite solid electrolytes (CSEs) are relatively advantageous solid-state electrolytes, they also face severe challenges. This review summarizes the main stability issues related to chemical, mechanical, thermal, and electrochemical aspects faced by ISEs and CSEs. The corresponding state-of-the-art improvement strategies have been proposed, including filling of modified particles, electrolyte pore adjustment, electrolyte internal structure arrangement, and interface modification.

The influence of cerium oxide content on the crack growth in zirconia ceramic materials for engineering applications

This article proposes a method of using cerium oxide and zirconium oxide to prepare ceramic materials for cold welding equipment in the production of lithium batteries. Injecting ceria and other metal oxides can transform zirconia from martensite into a stable four cubic lattice. By increasing the content of cerium oxide above 9%, the monoclinic crystal is transformed to tetragonal phase, and further increase to 10%–15% is beneficial to transform the tetragonal crystal state or the cubic crystal phase into a complete solid solution. When cooled from a high temperature (2293 °C) to room temperature, ceria-doped zirconia presented a tetragonal phase structure without changing into a monoclinic phase. It was also demonstrated that the crack tip at the front of the material has a shielding effect on the tetragonal phase. In particular, it was found that the flexural strength of the material reached 800 MPa, indicating that the developed zirconia-based ceramic composite material has the ability to replace diamond knives. The current work has confirmed the possibility of obtaining new ceramic materials with different characteristics by reasonably distributing the ingredients and appropriately controlling the content of cerium oxide or other metal oxides.