Power Lithium-ion Batteries Research Articles

A State-of-Health Estimation Method of a Lithium-Ion Power Battery for Swapping Stations Based on a Transformer Framework

Against the backdrop of automobile electrification, an increasing number of battery-swapping stations for electric vehicles have been launched to address the issue of slow battery charging under cold temperature conditions. However, due to the separation of the discharging and charging processes for lithium-ion batteries (LIBs) at swapping stations, and the circulation of batteries across different vehicles and stations, the operating data become fragmented, making it difficult to accurately identify the battery state-of-health (SOH). This study proposes a BiLSTM-Transformer framework that extracts the Constant Voltage Time (CVT) feature using only charging data, enabling the precise estimation of battery capacity degradation. Validation experiments conducted on battery samples under different operating temperatures showed that the model achieved a normalized RMSE of less than 1.6%. In ideal conditions, the normalized RMSE of the estimation reached as low as 0.11%. This model enables SOH estimation without relying on discharge data, contributing to the efficient and safe operation of battery swapping stations.

Research on the Fast Charging Strategy of Power Lithium-Ion Batteries Based on the High Environmental Temperature in Southeast Asia

To address the problem of excessive charging time for electric vehicles (EVs) in the high ambient temperature regions of Southeast Asia, this article proposes a rapid charging strategy based on battery state of charge (SOC) and temperature adjustment. The maximum charging capacity of the cell is exerted within different SOCs and temperature ranges. Taking a power lithium-ion battery (LIB) with a capacity of 120 Ah as the research object, a rapid charging model of the battery module was established. The battery module was cooled by means of a liquid cooling system. The combination of the fast charging strategy and the cooling strategy was employed to comprehensively analyze the restrictions of the fast charging rate imposed by the battery SOC and temperature. The results indicate that when the coolant flow rate was 12 L/min and the inlet coolant temperature was 22 °C, the liquid cooling system possessed the optimal heat exchange capacity and the lowest energy consumption. The maximum temperature (Tmax) of the battery during the charging process was 50.04 °C, and the charging time was 2634 s. To lower the Tmax of the battery during the charging process, a charging rate limit was imposed on the temperature range above 48 °C based on the original fast charging strategy. The Tmax decreased by 0.85 °C when charging with the optimized fast charging strategy.

Intellectual property analysis of recycling technologies for spent power lithium-ion batteries

The rapid expansion and increasing adoption of electric vehicles have significantly amplified the demand for power batteries, making the recycling and treatment of spent power lithium-ion batteries a critical issue for environmental protection and resource conservation. Actively pursuing the development of eco-friendly recycling technologies and enhancing the regulatory frameworks governing the disposal of spent power lithium-ion batteries are concerns worldwide. This paper places a particular emphasis on the role of intellectual property protection in the advancement of spent power lithium-ion battery recycling technologies. By classifying the key technologies in the recycling process, reviewing recent policies and regulations, and conducting a comprehensive analysis of patent applications related to these technologies, this study applies intellectual property analysis to systematically investigate the global trends in technology development, the main technological players, and the key fields of innovation in spent power lithium-ion battery recycling over the past two decades. The findings underscore the crucial influence of intellectual property protection on fostering technological innovation and driving the global advancement of recycling technologies. Finally, the paper summarizes the technical characteristics, focal areas, challenges, and future prospects of spent power lithium-ion battery recycling technologies in the context of global energy transformation and sustainable development, providing strategic guidance for future industrialization, technological innovation, and research directions in this critical field.

A Review on Leaching of Spent Lithium Battery Cathode Materials Adopting Deep Eutectic Solvents.

As a result of the swift surge in the adoption of electric vehicles, the quantity of spent lithium-ion power batteries has been growing at an exponential rate. Improper handling of these batteries can lead to the waste of strategic metal resources and pose risks to the environment and human health. Without doubt, it is essential to scientifically recover and reuse these spent power batteries, particularly by recovering positive electrode materials. Currently, there are several methods for recovering positive electrode materials, including pyrometallurgy, hydrometallurgy, bioleaching, and deep eutectic solvents (DESs) leaching. This review concetrated on the emerging technology of DESs leaching for positive electrode materials in spent lithium-ion battery. It provided an overview of the latest advancements in DESs leaching, considering factors such as acidity, reducibility, and coordination of DESs. The current technical status was analyzed and discussed, while also addressing the challenges and prospects for the development of DESs recovery in spent Li-ion power batteries. This work aims to offer practical guidance and serve as a foundation for additional studies and widespread implementation of DESs leaching for positive electrode materials.

Enhancing the cycling stability of Ni-rich cathodes via dual-site modification induced by slight Ti-rich doping

The Ni-rich cathode material LiNi0.90Co0.05Mn0.05O2 is a promising candidate for power lithium-ion batteries due to its high specific capacity. However, it suffers from inherent structural instability and severe interfacial side reactions, leading to rapid capacity degradation and thermal instability. In this study, we employed a slight Ti-rich doping strategy to enhance the structural and interfacial stability of the LiNi0.90Co0.05Mn0.05O2 cathode. The slight Ti-rich doping achieves dual-site modification (TM and Li), inhibits the anisotropic lattice changes, and improves the reversibility of electrochemical reactions. Additionally, it induces the formation of a Li2TiO3 coating on the particle surface, which inhibits interfacial side reactions, reduces the deposition of decomposition products, and enhances thermal stability. This strategy significantly improves the cycling stability of the LiNi0.90Co0.05Mn0.05O2 cathode, achieving a capacity retention rate of 94.4 % at 1C after 150 cycles. This effective approach paves the way for enhancing the electrochemical performance of Ni-rich cathodes.

Analysis of Factors Affecting the Import and Export of New Energy Products

With global warming and climate change becoming more and more serious, countries around the world have begun to pay attention to emission reduction and environmental protection, and the concept of ‘dual carbon’ has further penetrated into people's hearts, bringing new opportunities for the export of power lithium batteries from China. This paper aims to conduct a digital analysis of the export trade of the top seven countries (regions) in terms of the volume of power lithium battery trade in China, and to explore the influencing factors of the export volume of power lithium batteries from China. This paper first conducts a contour analysis based on the data fluctuations of five indicators in 32 provinces (excluding Hong Kong, Macao and Taiwan) from 2019 to 2021: total carbon dioxide emissions (mt), lithium iron phosphate production (10,000 tons), lithium battery electrolyte (10,000 tons), two-wheeled electric vehicles (100,000 vehicles), and lithium battery separators (10,000 tons). The final conclusion is that the ‘dual carbon’ background has a significant impact on China's power lithium battery industry. Furthermore, based on a panel data regression model, the factors affecting trade between China and the major countries (regions) exporting power lithium batteries are explored in depth. The results of the analysis found that the power generation, economic freedom, number of charging piles, population size, and per capita GDP of the exporting countries significantly affect the export volume of power lithium batteries in China. Among them, the population size and per capita GDP growth rate of the exporting countries have a negative impact, while the rest have a positive impact on the export volume of power lithium batteries in China.

Intelligent solar light electric vehicle moving in hot regions under a hybrid power source strategy

Solar Light Electric Vehicles (ISLEV) have recently gained increasing attention as a promising solution for sustainable transportation. In hot regions, such as the BECHAR region in southwest Algeria, where temperatures can exceed 50 °C, the challenge of maintaining high performance standards while coping with challenging environmental conditions is critical. To address this challenge, this study proposes an intelligent hybrid power source strategy comprising SUN Power solar PV and lithium-ion battery supercapacitors. To optimize the vehicle's performance, a feedforward neural network FF-NN is employed, which regulates the power flow between the hybrid sources. The proposed system's efficiency and effectiveness are assessed through simulations, which reveal its robustness in coping with challenging environmental conditions while maintaining high performance standards. The results show that the proposed system holds con-siderable potential for sustainable and efficient transportation in hot regions and can have broad applications in diverse sectors. Future industrial vehicle designs must incorporate the choice of hybrid power management into their planning process to ensure the efficient use of energy and optimize the vehicle's performance.

Research progress of aerogel used in lithium-ion power batteries

In recent years, with the rapid development of clean energy vehicles (i.e., electric vehicles and hybrid electric vehicles) and electrochemical energy storage stations, safety accidents have significantly increased. However, the abuse conditions such as overheating, overcharging, mechanical abuse, short circuits, etc., can result in thermal runaway of lithium-ion batteries (LIBs). Severe thermal runaway can lead to battery fire and even explosion, thereby threatening the safety of personnel. The application of a few aerogels to the thermal insulation layer between the cells of the lithium-ion battery modules can strengthen the safety of batteries. Among many aerogels, oxide aerogels show excellent insulation and high-temperature resistance. Therefore, aerogels, especially oxide aerogels, have aroused widespread research interest. This paper introduces the mechanism of thermal runaway of LIBs and systematically reviews several important oxide aerogels and the derived composites, especially those based on SiO2, Al2O3, and ZrO2 aerogels. The mechanical strength and high-temperature resistance of those aerogels are discussed. The application of aerogel in LIBs is also investigated in detail, and the all-around effect is caused by the introduction of aerogel materials. In addition, the thermal protection safety strategy of aerogel thermal insulation layers is proposed. It is supposed that this review could enable readers to deepen their understanding of this field.

A Fault Diagnosis Method for Electric Vehicle Lithium Power Batteries Based on Dual Feature Extraction from the Time and Frequency Domains

Abstract This study focuses on the safety and reliability issues of lithium-ion batteries, proposing a fault diagnosis strategy that leverages dual feature extraction in the time-frequency domains. Additionally, by modifying the traditional autoencoder, the study proposes a feature-guided autoencoder as an unsupervised model for extracting features in the time domain. Initially, wavelet packet decomposition and its energy denoising treatment are employed to refine fault information within battery voltage signals. Subsequently, the reconstruction error outputted by the Feature-Guided Autoencoder is utilized as the time-domain fault feature, while the cosine similarity of the energy of signals in various frequency bands obtained after wavelet packet decomposition serves as the frequency-domain fault feature. Ultimately, this paper selects the Isolation Forest algorithm for two-dimensional outlier detection of time-frequency features. Experimental results demonstrate that the Feature-Guided Autoencoder proposed in this study not only enhances the sensitivity of time-domain fault features compared to traditional autoencoders and their variants but also optimizes issues related to training time and computational load. The effectiveness of the proposed dual feature fault diagnosis method in both the time and frequency domains is validated through data from two actual vehicles, showing superior early fault detection capability relative to single-feature fault diagnosis methods.

Exploration of physical recovery techniques and economic viability for retired lithium nickel cobalt manganese oxide-type lithium-ion power batteries

Exploration of physical recovery techniques and economic viability for retired lithium nickel cobalt manganese oxide-type lithium-ion power batteries

Multi-Scenario Deep Learning-Based Framework to Estimate the Remaining Charge Time of Lithium-Ion Power Batteries

Multi-Scenario Deep Learning-Based Framework to Estimate the Remaining Charge Time of Lithium-Ion Power Batteries

Simulation analysis of low-temperature heat generation of power batteries based on the ECM model

Abstract When the power battery operates in low temperatures, it encounters challenges with charging and discharging, leading to a decline in battery performance, which can prevent electric vehicles from starting and reduce their driving range. To address this, the battery must possess the capability to adapt to both extremely high and low temperatures. This article employs ANSYS software to investigate the heat generation in batteries due to their own charging and discharging processes at different discharge rates under -20°C. When the battery is heated at a 1 C discharge rate for 20 minutes, its temperature rises by approximately 1.1°C; at 2 C, the temperature rises by about 5°C; and at 3 C, it rises by about 11°C. The greater the discharge rate is, the more heat is generated, resulting in a higher temperature rise. Furthermore, prolonged heating at a certain discharge rate can elevate the temperature to a level that is optimal for lithium-iron-phosphate batteries, ultimately reaching their optimal operating range. This research contributes to enabling lithium-ion power batteries to function normally in low-temperature environments, without compromising their lifespan. It is imperative to heat the interior of lithium-ion power batteries to ensure they can start normally after prolonged overnight parking, through preheating.

Advancements and Current Developments in Integrated System Architectures of Lithium-Ion Batteries for Electric Mobility

Recognizing the challenges faced by power lithium-ion batteries (LIBs), the concept of integrated battery systems emerges as a promising avenue. This offers the potential for higher energy densities and assuaging concerns surrounding electric vehicle range anxiety. Moreover, mechanical design optimization, though previously overlooked, is gaining traction among researchers as a viable alternative to achieve enhanced energy and power densities. This review paper provides a comprehensive overview of recent research and progress in this domain, emphasizing the significance of battery architectures in enabling the widespread adoption of electric mobility. Beginning with an exploration of fundamental principles underlying LIB systems, the paper discusses various architectures involving different cell form factors, like pouch cells, cylindrical cells, and prismatic cells, along with their advantages and limitations. Furthermore, it reviews recent research trends, highlighting innovations aimed at enhancing battery performance, energy density, and safety through advanced battery system architecture. Through case studies and discussions on challenges and future directions, the paper underscores the critical role of advanced battery system architecture in driving the evolution of e-mobility and shaping the sustainable transportation landscape.

Thermal Runaway and Thermal Management of Lithium-Ion Power Batteries in New Energy Vehicles

Thermal Runaway and Thermal Management of Lithium-Ion Power Batteries in New Energy Vehicles

Nontarget Analysis of Legacy and Emerging PFAS in a Lithium-Ion Power Battery Recycling Park and Their Possible Toxicity Measured Using High-Throughput Phenotype Screening.

Driven by the global popularity of electric vehicles and the shortage of critical raw materials for batteries, the spent lithium-ion power battery (LIPB) recycling industry has exhibited explosive growth in both quantity and scale. However, relatively little information is known about the environmental risks posed by LIPB recycling, in particular with regards to perfluoroalkyl and polyfluoroalkyl substances (PFAS). In this work, suspect screening and nontarget analysis were carried out to characterize PFAS in soil, dust, water and sediment from a LIPB recycling area. Twenty-five PFAS from nine classes were identified at confidence level 3 or above, including 13 legacy and 12 emerging PFAS, as well as two ultrashort-chain PFAS. Based on the target analysis of 16 PFAS, at least nine were detected in each environmental sample, indicating their widespread presence in a LIPB recycling area. Perfluorodecanoic acid, perfluorooctanesulfonic acid and trifluoromethanesulfonamide showed significant differences in the four phenotypic parameters (growth, movement, survival and fecundity) of Caenorhabditis elegans and were the most toxic substances in all target PFAS at an exposure concentration of 200 μM. Our project provides first-hand information on the existence and environmental risk of PFAS, facilitating the formulation of regulations and green development of the LIPB recycling industry.

High ionic conductivity materials Li3YBr6 and Li3LaBr6 for solid-state batteries: first-principles calculations

High ionic conductivity solid-state electrolytes are essential for powerful solid-state lithium-ion batteries. With density functional theory andab initiomolecular dynamics simulations, we investigated the crystal structures of Li3YBr6and Li3LaBr6. The lowest energy configurations with uniform distribution of lithium ions were identified. Both materials have wide electrochemical stability windows (ESW): 2.64 V and 2.57 V, respectively. The experimental ESW for Li3YBr6is 2.50 V. Through extrapolating various temperature diffusion results, the conductivity of Li3YBr6was obtained at room temperature, approximately 3.9 mS cm-1, which is comparable to the experimental value 3.3 mS cm-1. Li3LaBr6has a higher conductivity, a 100% increase compared with Li3YBr6. The activation energies of Li3YBr6and Li3LaBr6through the Arrhenius plot are 0.26 eV and 0.24 eV, respectively, which is also close to the experimental value of 0.30 eV for Li3YBr6. This research explored high ionic conductivity halide materials and will contribute to developing solid-state lithium-ion batteries.

Study on the interface of high specific energy High stability

High nickel terterial oxide, with high specific capacity and low cost advantages, is the preferred positive electrode for high specific energy lithium-ion power batteries at present. However, the high nickel ternary cathode material is easy to have side reactions with the electrolyte in the high delithium state, which can not only lead to the dissolution of transition metal ions and the formation of the surface salt phase, but also cause the lattice oxygen loss and surface interface side reactions, resulting in rapid attenuation of electrode capacity. In this paper, the development history and structural characteristics of high nickel ternary cathode materials are introduced, and the surface interface problems leading to capacity attenuation and structural degradation are comprehensively analyzed. From this perspective, three effective strategies for improving electrochemical performance of high nickel ternary cathode materials are summarized. Finally, by describing the advantages and disadvantages of these layered cathode materials, the challenges faced by these layered cathode materials are discussed, and it is pointed out that in the future, composite modification strategies should be adopted to optimize their structures and improve their properties.

Prediction of the health state of lithium-ion power batteries using machine learning

Faced with the increasingly urgent issues of energy depletion and environmental pollution, various countries are actively supporting the new energy vehicle industry, making electric vehicle technology a focus of widespread attention among researchers. The Battery Management System (BMS) plays a crucial role in overseeing the power battery's operational parameters, with the estimation of the State of Health (SOH) being a pivotal function. Accurate estimation of SOH can improve the utilization efficiency and endurance of power batteries, extend their service life, and help users achieve the best balance between system safety and economic benefits. Machine learning methods provide a new solution to the SOH estimation problem. Without analyzing the complex aging mechanisms inside the battery, online SOH estimation can be completed by learning from historical aging data. In this study, the lithium battery dataset provided by NASA is used and trained through multiple linear regression models and support vector machine models to predict the SOH of lithium-ion batteries. The results demonstrate the accuracy and reliability of both methods in predicting SOH. Simultaneously, the prediction results of different feature values are compared to obtain the most accurate combination of feature values.

An Improved Collaborative Estimation Method for Determining The SOC and SOH of Lithium-Ion Power Batteries for Electric Vehicles

With the increase in the amount of actual operating data on electric vehicles, how to analyze and process useful information from existing battery charging and discharging data and apply it to subsequent state estimation is worthy of in-depth thinking and practice by researchers. This article proposes a collaborative estimation architecture for SOC and SOH based on the 1RC equivalent circuit model, recursive least squares, and adaptive extended Kalman filtering algorithms (AEKF), which combine offline data processing with online applications. By applying offline data processing, OCV–SOC polynomial fitting and average polarization resistance were determined, which reduced the time required for basic data measurement and improved the accuracy of model parameter identification, while a recursive estimation combining micro- and macro-time-scales of AEKF was used for the online real-time estimation of the SOC and actual available capacity of batteries, in order to eliminate interference from measurement and process noise. The results of the simulated and experimental data validation indicate that the proposed algorithm is applicable to the lithium-ion batteries studied in this paper, the average SOC deviation is less than 1.5%, the maximum deviation is less than 2.02%, and the SOH estimation deviation is less than 1% under different driving conditions in the multi-temperature range. This study lays the foundation for further utilizing offline data and improving SOC and SOH collaborative estimation algorithms.

Real time prediction algorithm for SOC of lithium ion power battery under high pulse rate

Real time prediction algorithm for SOC of lithium ion power battery under high pulse rate