Batteries

18 pages, 3297 KB

Open AccessArticle

A Framework for Anomaly Cell Detection in Energy Storage Systems Based on Daily Operating Voltage and Capacity Increment Curves

by Wanchen Liu, Zhihao Zhang, Zekai Zhao and Wenjie Zhang

Batteries 2025, 11(8), 316; https://doi.org/10.3390/batteries11080316 - 20 Aug 2025

Abstract

This paper proposes a novel unsupervised multi-model fusion framework for robust cell-level anomaly detection in grid-scale battery energy storage systems (BESSs). Addressing the complex nonlinearity and prevalent data quality issues (e.g., asynchronous sensors, sampling anomalies) in historical operational data, the framework synergistically integrates [...] Read more.

This paper proposes a novel unsupervised multi-model fusion framework for robust cell-level anomaly detection in grid-scale battery energy storage systems (BESSs). Addressing the complex nonlinearity and prevalent data quality issues (e.g., asynchronous sensors, sampling anomalies) in historical operational data, the framework synergistically integrates three complementary techniques: isolation forests for efficient feature screening and dimensionality reduction; LSTM autoencoders to capture the long-term temporal dependencies in normal behavior; and a functional principal component analysis–Mahalanobis distance (FPCA-MD) for statistically rigorous anomaly validation. The fully automated workflow pioneers the combined application of feature screening, temporal modeling, and functional data validation for cell-level diagnostics. Key contributions include (1) maintaining a high detection accuracy despite asynchronous or faulty sensor data; (2) leveraging multi-dimensional operational features beyond traditional voltage curves, optimizing the utilization of historical data through tight integration of the battery characteristics with anomaly signatures; and (3) achieving enhanced performance and robustness via the complementary fusion of diverse algorithms. Comprehensive experimental results demonstrate the framework’s effectiveness in accurately identifying cells exhibiting various anomaly patterns (e.g., noise interference, performance degradation, cluster outliers) while significantly reducing the leakage and misdetection rates inherent in single-algorithm approaches, as validated by the probability scores from the fusion output. Full article

► Show Figures

Figure 1

31 pages, 7431 KB

Open AccessReview

Breaking the Polarization Bottleneck: Innovative Pathways to High-Performance Metal–Air Batteries

by Biao Ma, Deling Hong, Xiangfeng Wei and Jiehua Liu

Batteries 2025, 11(8), 315; https://doi.org/10.3390/batteries11080315 - 19 Aug 2025

Abstract

Metal–air batteries have excellent theoretical energy density and economic advantages through abundant anode materials and open cathode structures. However, the actual energy efficiency of metal–air batteries is much lower than the theoretical value due to the effect of polarization voltage during battery operation, [...] Read more.

Metal–air batteries have excellent theoretical energy density and economic advantages through abundant anode materials and open cathode structures. However, the actual energy efficiency of metal–air batteries is much lower than the theoretical value due to the effect of polarization voltage during battery operation, limiting the power output and thus hindering their practical application. This review systematically dissects the origins of polarization: slow oxygen reduction/evolution reaction (ORR/OER) kinetics, interfacial resistance, and mass transfer bottlenecks. We highlight cutting-edge strategies to mitigate polarization, including atomic-level engineering of air cathodes (e.g., single-atom catalysts, low Pt catalysts), biomass-derived 3D porous electrodes, and electrolyte innovations (additives to inhibit corrosion, solid-state electrolytes to improve stability). In addition, breakthroughs in metal–H₂O₂ battery design using concentrated liquid oxygen sources are discussed. Together, these advances alleviate the battery polarization bottleneck and pave the way for practical applications of metal–air batteries in electric vehicles, drones, and deep-sea devices. Full article

(This article belongs to the Special Issue Batteries: 10th Anniversary)

► Show Figures

Graphical abstract

18 pages, 13041 KB

Open AccessArticle

Experimental Testing and Modeling of Li-Ion Battery Performance Based on IEC 62660-1 Standard

by Zoi Voltsi and Costas Elmasides

Batteries 2025, 11(8), 314; https://doi.org/10.3390/batteries11080314 - 17 Aug 2025

Abstract

The adoption of sustainable and environmentally friendly solutions is becoming crucial across several sectors, particularly in transportation. As part of this transition, the transport industry has turned its attention to electric vehicle (EV) development and the deployment of electric batteries. This study provides [...] Read more.

The adoption of sustainable and environmentally friendly solutions is becoming crucial across several sectors, particularly in transportation. As part of this transition, the transport industry has turned its attention to electric vehicle (EV) development and the deployment of electric batteries. This study provides a comprehensive analysis of the performance of EV batteries, integrating both experimental measurements and simulations. The experimental section involved a series of tests conducted on real batteries under various operating conditions, focusing on different charging and discharging rates. Additionally, the IEC 62660-1 standard was applied, to evaluate their performance under realistic usage scenarios. Moreover, a theoretical model was developed in order to simulate the batteries’ behavior and replicate the observed experimental data. A comparison between the simulation outputs and experimental data was conducted, demonstrating the accuracy of the model. This work provides valuable insights into the performance of EV batteries and lays the foundation for optimization in future applications. Full article

(This article belongs to the Special Issue Advances in Battery Modeling: Models, Charging Strategies, Performance Estimations and Thermal Management)

► Show Figures

Figure 1

21 pages, 3124 KB

Open AccessArticle

Systematic Characterization of Lithium-Ion Cells for Electric Mobility and Grid Storage: A Case Study on Samsung INR21700-50G

by Saroj Paudel, Jiangfeng Zhang, Beshah Ayalew and Rajendra Singh

Batteries 2025, 11(8), 313; https://doi.org/10.3390/batteries11080313 - 16 Aug 2025

Abstract

Accurate parametric modeling of lithium-ion batteries is essential for battery management system (BMS) design in electric vehicles and broader energy storage applications, enabling reliable state estimation and effective thermal control under diverse operating conditions. This study presents a detailed characterization of lithium-ion cells [...] Read more.

Accurate parametric modeling of lithium-ion batteries is essential for battery management system (BMS) design in electric vehicles and broader energy storage applications, enabling reliable state estimation and effective thermal control under diverse operating conditions. This study presents a detailed characterization of lithium-ion cells to support advanced BMS in electric vehicles and stationary storage. A second-order equivalent circuit model is developed to capture instantaneous and dynamic voltage behavior, with parameters extracted through Hybrid Pulse Power Characterization over a broad range of temperatures (−10 °C to 45 °C) and state-of-charge levels. The method includes multi-duration pulse testing and separates ohmic and transient responses using two resistor–capacitor branches, with parameters tied to physical processes like charge transfer and diffusion. A weakly coupled electro-thermal model is presented to support real-time BMS applications, enabling accurate voltage, temperature, and heat generation prediction. This study also evaluates open-circuit voltage and direct current internal resistance across pulse durations, leading to power capability maps (“fish charts”) that capture discharge and regenerative performance across SOC and temperature. The analysis highlights performance asymmetries between charging and discharging and confirms model accuracy through curve fitting across test conditions. These contributions enhance model realism, thermal control, and power estimation for real-world lithium-ion battery applications. Full article

(This article belongs to the Special Issue Enhancement of Lithium-Ion and Post-lithium Batteries Safety: Fundamentals, Materials and Applications)

► Show Figures

Figure 1

24 pages, 6274 KB

Open AccessArticle

Accurate Prediction of Voltage and Temperature for a Sodium-Ion Pouch Cell Using an Electro-Thermal Coupling Model

by Hekun Zhang, Zhendong Zhang, Yelin Deng and Jianxu Yu

Batteries 2025, 11(8), 312; https://doi.org/10.3390/batteries11080312 - 16 Aug 2025

Abstract

Due to their advantages, such as abundant raw material reserves, excellent thermal stability, and superior low-temperature performance, sodium-ion batteries (SIBs) exhibit significant potential for future applications in energy storage and electric vehicles. Therefore, in this study, a commercial pouch-type SIB with sodium iron [...] Read more.

Due to their advantages, such as abundant raw material reserves, excellent thermal stability, and superior low-temperature performance, sodium-ion batteries (SIBs) exhibit significant potential for future applications in energy storage and electric vehicles. Therefore, in this study, a commercial pouch-type SIB with sodium iron sulfate cathode material was investigated. Firstly, a second-order RC equivalent circuit model was established through parameter identification using multi-rate hybrid pulse power characterization (M-HPPC) tests at various temperatures. Then, both the specific heat capacity and entropy coefficient of the sodium-ion battery were measured through experiments. Building upon this, an electro-thermal coupling model was developed by incorporating a lumped-parameter thermal model that accounts for the heat generation of the tabs. Finally, the prediction performance of this model was validated through discharge tests under different temperature conditions. The results demonstrate that the proposed electro-thermal coupling model can achieve the simultaneous prediction of both temperature and voltage, providing valuable references for the future development of thermal management systems for SIBs. Full article

(This article belongs to the Special Issue Batteries: 10th Anniversary)

► Show Figures

Figure 1

14 pages, 8711 KB

Open AccessArticle

Intrinsic Thermal Stability of Li-Rich Mn-Based Cathodes Enabling Safe High-Energy Lithium-Ion Batteries

by Zhaoqiang Pei, Shaobo Feng, Zhibo Han, Zihua Wang, Chengshan Xu, Xiangming He, Li Wang, Yu Wang and Xuning Feng

Batteries 2025, 11(8), 311; https://doi.org/10.3390/batteries11080311 - 15 Aug 2025

Abstract

Lithium-rich manganese-based oxides (LMR) are promising next-generation cathode materials due to their high capacity and low cost, but safety remains a critical bottleneck restricting the practical application of high-energy-density cathodes. However, the safety level of LMR batteries and the thermal failure mechanism of [...] Read more.

Lithium-rich manganese-based oxides (LMR) are promising next-generation cathode materials due to their high capacity and low cost, but safety remains a critical bottleneck restricting the practical application of high-energy-density cathodes. However, the safety level of LMR batteries and the thermal failure mechanism of the cathode are still poorly understood, especially when compared with traditional high-energy nickel-rich (Ni-rich) cathodes. Here, we investigate the LMR cell’s thermal runaway behavior and the thermal failure mechanism of the cathode. Compared to a Ni-rich cell, Accelerating Rate Calorimetry (ARC) shows the LMR pouch cell exhibits a 62.7 °C higher thermal runaway trigger temperature (T2) and 270.3 °C lower maximum temperature (T3). These results indicate that the cell utilizing a higher-energy-density LMR cathode presents significantly lower thermal runaway risks and hazards. The results of differential scanning calorimetry–thermogravimetry–mass spectrometry (DSC-TG-MS) and in situ heating X-ray diffraction (XRD) indicate that the LMR cathode has superior thermal stability compared with the Ni-rich cathode, with cathode oxygen released at higher temperatures and lower rates, which is beneficial for delaying and mitigating the exothermic reaction inside the battery. This study demonstrates that simultaneously enhancing cathode energy density and battery safety is achievable, and these findings provide theoretical guidance for the design of next-generation high-energy and high-safety battery systems. Full article

(This article belongs to the Special Issue Thermal Management System for Lithium-Ion Batteries: 2nd Edition)

► Show Figures

Graphical abstract

18 pages, 4380 KB

Open AccessArticle

Exploring the Potential of Green Synthesized Sr_0.8Ce_0.2Fe_0.8Co_0.2O₃ Using Orange and Lemon Extracts for Hybrid Supercapacitor Applications

by Asmara Fazal, M. Javaid Iqbal, Mohsin Ali Raza, Badriah S. Almutairi, Hesham M. H. Zakaly, Naureen Akhtar, Muneeb Irshad and Saira Riaz

Batteries 2025, 11(8), 310; https://doi.org/10.3390/batteries11080310 - 15 Aug 2025

Abstract

Supercapacitors are required to store energy from renewable resources to ensure a pollutant-free environment. To further encourage its study, researchers are interested in introducing green methods to produce electrode materials. Green synthesis is an innovative and emerging field because plant extracts are the [...] Read more.

Supercapacitors are required to store energy from renewable resources to ensure a pollutant-free environment. To further encourage its study, researchers are interested in introducing green methods to produce electrode materials. Green synthesis is an innovative and emerging field because plant extracts are the best substitute for toxic chemicals. They are considered eco-friendly and cost-effective. In this work, two plant extracts, orange juice (ORJ) and lemon juice (LMJ), are used to synthesize the Sr_0.8Ce_0.2Fe_0.8Co_0.2O₃ perovskite using the auto-combustion method. The electrochemical performance of Sr_0.8Ce_0.2Fe_0.8Co_0.2O₃ made from LMJ and ORJ is compared to check their effectiveness. LMJ proved to be a better reducing agent than ORJ with a higher specific capacity of 300 C/g (544 F/g) at 1 A/g current density due to increased oxygen vacancies and surface area. These findings show that green-synthesized perovskites can be utilized in high-performance hybrid supercapacitor devices. Full article

(This article belongs to the Section Supercapacitors)

► Show Figures

Graphical abstract

21 pages, 2683 KB

Open AccessArticle

Referential Integrity Framework for Lithium Battery Characterization and State of Charge Estimation

by Amel Benmouna, Mohamed Becherif, Mohamed Ahmed Ebrahim, Mohamed Toufik Benchouia, Tahir Cetin Akinci, Miroslav Penchev, Alfredo Martinez-Morales and Arun S. K. Raju

Batteries 2025, 11(8), 309; https://doi.org/10.3390/batteries11080309 - 14 Aug 2025

Abstract

The global rise of electric vehicles (EVs) is reshaping the automotive industry, driven by a 25% increase in EV sales in 2024 and mounting regulatory pressure from European countries aiming to phase out thermal and hybrid vehicle production. In this context, the development [...] Read more.

The global rise of electric vehicles (EVs) is reshaping the automotive industry, driven by a 25% increase in EV sales in 2024 and mounting regulatory pressure from European countries aiming to phase out thermal and hybrid vehicle production. In this context, the development of advanced battery technologies has become a critical priority. However, progress in electrochemical storage systems remains limited due to persistent technological barriers such as gaps in data, inadequate modeling tools, and difficulties in system integration, such as thermal management and interface instability. Safety concerns like thermal runaway and the lack of long-term performance data also hinder large-scale adoption. This study presents an in-depth analysis of lithium–ion (Li–ion) batteries, with a particular focus on evaluating their charging and discharging behaviors. To facilitate this, a series of automated experiments was conducted using a custom-built test bench equipped with MATLAB (2024b) programming and dSPACE data acquisition cards, enabling precise current and voltage measurements. The acquired data were analyzed to derive mathematical models that capture the operational characteristics of Li–ion batteries. Furthermore, various state-of-charge (SoC) estimation techniques were investigated to enhance battery efficiency and improve range management in EVs. This paper contributes to the advancement of energy storage technologies and supports global ecological goals by proposing safer and more efficient solutions for the electric mobility sector. Full article

(This article belongs to the Special Issue Advances in Battery Electric Vehicles—2nd Edition)

► Show Figures

Figure 1

11 pages, 1962 KB

Open AccessArticle

Cu-Substituted Na₃V₂(PO₄)₃/C Composites as High-Rate, Long-Cycle Cathodes for Sodium-Ion Batteries

by Hyeon-Jun Choi, Yu Gyeong Kim, Su Hwan Jeong, Sang Jun Lee, Young Hwa Jung and Joo-Hyung Kim

Batteries 2025, 11(8), 308; https://doi.org/10.3390/batteries11080308 - 11 Aug 2025

Abstract

The advancement of high-performance sodium-ion batteries (SIBs) necessitates cathode materials that exhibit both structural robustness and long-term electrochemical stability. Na₃V₂(PO₄)₃ (NVP), with its NASICON-type framework, is a promising candidate; however, its inherently low electronic conductivity restricts [...] Read more.

The advancement of high-performance sodium-ion batteries (SIBs) necessitates cathode materials that exhibit both structural robustness and long-term electrochemical stability. Na₃V₂(PO₄)₃ (NVP), with its NASICON-type framework, is a promising candidate; however, its inherently low electronic conductivity restricts full capacity utilization. In this study, carbon-coated and Cu-substituted Na₃V₂(PO₄)₃ (NVCP) composites were synthesized via a solid-state reaction using agarose as a carbon source. Structural and morphological analyses confirmed the successful incorporation of Cu²⁺ ions into the rhombohedral lattice without disrupting the crystal structure and the formation of uniform conductive carbon layers. The substitution of Cu²⁺ induced increased carbon disorder and partial oxidation of V³⁺ to V⁴⁺, contributing to enhanced electronic conductivity. Consequently, NVCP exhibited excellent long-term cycling performance, maintaining over 99% of its initial capacity after 500 cycles at 0.5 C. Furthermore, the electrode demonstrated outstanding high-rate capabilities, with a capacity recovery of 97.98% after cycling at 20 C and returning to lower current densities. These findings demonstrate that Cu substitution combined with carbon coating synergistically enhances structural integrity and Na⁺ transport, offering an effective approach to engineer high-performance cathodes for next-generation SIBs. Full article

(This article belongs to the Section Battery Materials and Interfaces: Anode, Cathode, Separators and Electrolytes or Others)

► Show Figures

Figure 1

28 pages, 1374 KB

Open AccessArticle

A Circuital Equivalent for Supercapacitors Accurate Simulation in Power Electronics Systems

by Catalina Rus-Casas, Carlos Andrés Ramos-Paja, Sergio Ignacio Serna-Garcés, Carlos Gilabert-Torres and Juan Domingo Aguilar-Peña

Batteries 2025, 11(8), 307; https://doi.org/10.3390/batteries11080307 - 9 Aug 2025

Abstract

The effective integration of energy storage systems is paramount for the widespread deployment of renewable energy technologies. Selection of a specific storage system is typically dictated by the primary challenge it aims to mitigate, such as intermittency, grid stability, or power quality. The [...] Read more.

The effective integration of energy storage systems is paramount for the widespread deployment of renewable energy technologies. Selection of a specific storage system is typically dictated by the primary challenge it aims to mitigate, such as intermittency, grid stability, or power quality. The optimization of overall system efficiency and longevity is increasingly achieved through hybrid storage systems that integrate supercapacitors into their designs. This research introduces a novel circuital equivalent for a commercial supercapacitor, optimized for precise simulations within the frequency range of power electronics applications. A key distinction of this circuital equivalent lies in its rigorous foundation: its comprehensive characterization across a broad frequency spectrum, specifically from 0.01 Hz to 300 kHz, employing a commercial frequency response analyzer. This precise circuital representation offers substantial utility in simulation, analysis, and design of high-frequency circuits, particularly for switched-power converter design and control. It enables the anticipation of undesirable phenomena, such as significant voltage ripple and operational instability. This predictive capability is crucial for experimental preparation, facilitating the proactive integration of necessary filters and protective measures within sensing circuits, thereby underscoring its value prior to physical implementation. In addition, the developed circuital equivalent exhibits broad compatibility, allowing seamless implementation within commercial circuit simulators. Finally, the proposed methodology was illustrated with a commercial supercapacitor, but it can be applied to other supercapacitor types or manufacturers. Full article

(This article belongs to the Special Issue High-Performance Supercapacitors: Preparation and Application—2nd Edition)

► Show Figures

Figure 1

13 pages, 10178 KB

Open AccessArticle

Luffa-like Interconnective Porous Nanofiber with Anchored Co/CoCr₂O₄ Hybrid Nanoparticles for Zinc–Air Batteries

by Guoqiang Jin, Bin Liu, Yan Liu, Xueting Zhang, Dapeng Cao and Xiuling Zhang

Batteries 2025, 11(8), 306; https://doi.org/10.3390/batteries11080306 - 8 Aug 2025

Abstract

The development of robust oxygen reduction reaction (ORR) catalyst with fast kinetics and good durability is significant for rechargeable zinc–air batteries (ZABs) but still remains a great challenge. Herein, inspired by the chain-like interconnective porous structure of plant luffa, an ORR catalyst of [...] Read more.

The development of robust oxygen reduction reaction (ORR) catalyst with fast kinetics and good durability is significant for rechargeable zinc–air batteries (ZABs) but still remains a great challenge. Herein, inspired by the chain-like interconnective porous structure of plant luffa, an ORR catalyst of Co/CoCr₂O₄@ IPCF is fabricated, with Co and CoCr₂O₄ hybrid nanoparticles (NPs) embedding into interconnective porous carbon nanofibers (IPCF). Contributing to CoCr₂O₄ NPs stabilized Co active sites, the resulting ZABs assembled with Co/CoCr₂O₄@IPCF as an air cathode catalyst delivering sustainable cycling stability of 550 h, surpassing that of Co@IPCF based on ZABs (215 h). Also, the Co/CoCr₂O₄@IPCF has a high ORR performance with a half-wave potential (E_1/2) of 0.866 V in alkaline medium. The cycling stability originates from the IPCF carrier and the synergistic effect of Co NPs and CoCr₂O₄ NPs. The chain-like interconnective porous structure of the fibers provides more active sites and facilitates mass transfer to avoid the accumulation of OH⁻ and the exposure of H₂O₂, while the CoCr₂O₄ NPs can serve as a regulator for stabilizing the Co NPs electrochemical performance. Full article

(This article belongs to the Special Issue Novel Materials for Rechargeable Batteries)

► Show Figures

Figure 1

11 pages, 1504 KB

Open AccessArticle

Nano-Alloy FeSb Wrapped in Three-Dimensional Honeycomb Carbon for High-Performance Lithium-Ion Batteries

by Nanjun Jia, Xinming Nie, Jianwei Li and Wei Qin

Batteries 2025, 11(8), 305; https://doi.org/10.3390/batteries11080305 - 8 Aug 2025

Abstract

Sb-based anodes have great potential in lithium-ion batteries because of their relatively high theoretical capacities. However, in general, their volume changes (>150%) during charge and discharge process have a significant impact, which affects their electrochemical performances. In this paper, nano-alloy FeSb wrapped in [...] Read more.

Sb-based anodes have great potential in lithium-ion batteries because of their relatively high theoretical capacities. However, in general, their volume changes (>150%) during charge and discharge process have a significant impact, which affects their electrochemical performances. In this paper, nano-alloy FeSb wrapped in three-dimensional honeycomb graphite carbon (FeSb@C) was prepared by the freeze-drying method using sodium chloride as a template. The three-dimensional carbon can buffer the volume change in the reaction process, increasing the contact area between the electrode and electrolyte. Furthermore, the addition of metallic iron also increases the overall specific capacity and improves its electrochemical performance. As the anode of a lithium-ion battery, the optimized FeSb@C shows excellent electrochemical performance with a specific capacity of 193.0 mAh g⁻¹ at a high current density of 5 A g⁻¹, and a reversible capacity of 607.8 mAh g⁻¹ after 600 cycles of 1 A g⁻¹. It provides an effective strategy for preparing high-performance lithium-ion batteries anode materials. Full article

(This article belongs to the Special Issue Batteries: 10th Anniversary)

► Show Figures

Figure 1

35 pages, 3497 KB

Open AccessReview

Recent Advances in Dendrite Suppression Strategies for Solid-State Lithium Batteries: From Interface Engineering to Material Innovations

by Abniel Machín, Francisco Díaz, María C. Cotto, José Ducongé and Francisco Márquez

Batteries 2025, 11(8), 304; https://doi.org/10.3390/batteries11080304 - 8 Aug 2025

Abstract

Solid-state lithium batteries (SSLBs) have emerged as a promising alternative to conventional lithium-ion systems due to their superior safety profile, higher energy density, and potential compatibility with lithium metal anodes. However, a major challenge hindering their widespread deployment is the formation and growth [...] Read more.

Solid-state lithium batteries (SSLBs) have emerged as a promising alternative to conventional lithium-ion systems due to their superior safety profile, higher energy density, and potential compatibility with lithium metal anodes. However, a major challenge hindering their widespread deployment is the formation and growth of lithium dendrites, which compromise both performance and safety. This review provides a comprehensive and structured overview of recent advances in dendrite suppression strategies, with special emphasis on the role played by the nature of the solid electrolyte. In particular, we examine suppression mechanisms and material innovations within the three main classes of solid electrolytes: sulfide-based, oxide-based, and polymer-based systems. Each electrolyte class presents distinct advantages and challenges in relation to dendrite behavior. Sulfide electrolytes, known for their high ionic conductivity and good interfacial wettability, suffer from poor mechanical strength and chemical instability. Oxide electrolytes exhibit excellent electrochemical stability and mechanical rigidity but often face high interfacial resistance. Polymer electrolytes, while mechanically flexible and easy to process, generally have lower ionic conductivity and limited thermal stability. This review discusses how these intrinsic properties influence dendrite nucleation and propagation, including the role of interfacial stress, grain boundaries, void formation, and electrochemical heterogeneity. To mitigate dendrite formation, we explore a variety of strategies including interfacial engineering (e.g., the use of artificial interlayers, surface coatings, and chemical additives), mechanical reinforcement (e.g., incorporation of nanostructured or gradient architectures, pressure modulation, and self-healing materials), and modifications of the solid electrolyte and electrode structure. Additionally, we highlight the critical role of advanced characterization techniques—such as in situ electron microscopy, synchrotron-based X-ray diffraction, vibrational spectroscopy, and nuclear magnetic resonance (NMR)—for elucidating dendrite formation mechanisms and evaluating the effectiveness of suppression strategies in real time. By integrating recent experimental and theoretical insights across multiple disciplines, this review identifies key limitations in current approaches and outlines emerging research directions. These include the design of multifunctional interphases, hybrid electrolytes, and real-time diagnostic tools aimed at enabling the development of reliable, scalable, and dendrite-free SSLBs suitable for practical applications in next-generation energy storage. Full article

(This article belongs to the Special Issue Advances in Solid Electrolytes and Solid-State Batteries)

► Show Figures

Graphical abstract

17 pages, 5360 KB

Open AccessArticle

Experimental and Numerical Study of the Impact of Pressure During the Pyrolysis of Diethyl Carbonate and Ethyl Methyl Carbonate

by Claire M. Grégoire, Eric L. Petersen and Olivier Mathieu

Batteries 2025, 11(8), 303; https://doi.org/10.3390/batteries11080303 - 8 Aug 2025

Abstract

During a thermal runaway, Lithium-ion battery cells are subjected to a large increase in temperature, which will vaporize and potentially thermally degrade their liquid electrolyte. The formation of gas in the battery cell will increase the pressure until the flammable gases vent and [...] Read more.

During a thermal runaway, Lithium-ion battery cells are subjected to a large increase in temperature, which will vaporize and potentially thermally degrade their liquid electrolyte. The formation of gas in the battery cell will increase the pressure until the flammable gases vent and potentially lead to a fire incident. While the pyrolysis chemistry of the electrolyte components has been studied near atmospheric pressure, the effect of pressure has not been investigated. This study was undertaken to better understand the effect of pressure on the thermal dissociation of two common linear electrolyte components, diethyl carbonate (DEC) and ethyl methyl carbonate (EMC). The pyrolysis of DEC and EMC was studied in the gas phase, in 99.75% He/Ar, and was carried out at high temperatures and for pressures near 5.5 atm. The time-resolved CO formation was measured using a quantum cascade laser, providing a unique experimental dataset. A detailed chemical kinetics analysis was performed to understand the effect of pressure on DEC and EMC, with CO time-history results obtained in similar conditions at near-atmospheric pressure for DEC and EMC serving as baselines for comparison. Numerical predictions using detailed chemical kinetics mechanisms from the literature were carried out, and reaction pathways at different pressures were highlighted to emphasize the effect of pressure on the pyrolysis chemistry. Full article

(This article belongs to the Special Issue Battery Thermal Performance and Management: Advances and Challenges)

► Show Figures

Figure 1

21 pages, 2537 KB

Open AccessArticle

State of Health Prediction of Lithium-Ion Batteries Based on Dual-Time-Scale Self-Supervised Learning

by Yuqi Li, Longyun Kang, Xuemei Wang, Di Xie and Shoumo Wang

Batteries 2025, 11(8), 302; https://doi.org/10.3390/batteries11080302 - 8 Aug 2025

Abstract

Accurate estimation of the state of health (SOH) of lithium-ion batteries confronts two critical challenges: the extreme scarcity of labeled data in large-scale operational datasets and the mismatch between existing methods (relying on full charging–discharging conditions) and shallow charging–discharging conditions prevalent in real-world [...] Read more.

Accurate estimation of the state of health (SOH) of lithium-ion batteries confronts two critical challenges: the extreme scarcity of labeled data in large-scale operational datasets and the mismatch between existing methods (relying on full charging–discharging conditions) and shallow charging–discharging conditions prevalent in real-world scenarios. To address these challenges, this study proposes a self-supervised learning framework for SOH estimation. The framework employs a dual-time-scale collaborative pre-training approach via masked voltage sequence reconstruction and interval capacity prediction tasks, enabling automatic extraction of cross-time-scale aging features from unlabeled data. Innovatively, it integrates domain knowledge into the attention mechanism and incorporates time-varying factors into positional encoding, significantly enhancing the capability to extract battery aging features. The proposed method is validated on two datasets. For the standard dataset, using only 10% labeled data, it achieves an average RMSE of 0.491% for NCA battery estimation and 0.804% for transfer estimation between NCA and NCM. For the shallow-cycle dataset, it achieves an average RMSE of 1.300% with only 2% labeled data. By synergistically leveraging massive unlabeled data and extremely sparse labeled samples (2–10% labeling rate), this framework reduces the labeling burden for battery health monitoring by 90–98%, offering an industrial-grade solution with near-zero labeling dependency. Full article

(This article belongs to the Topic Advanced Electric Vehicle Technology, 3rd Edition)

► Show Figures

Graphical abstract

36 pages, 13501 KB

Open AccessReview

Research Progress on Risk Prevention and Control Technology for Lithium-Ion Battery Energy Storage Power Stations: A Review

by Weihang Pan

Batteries 2025, 11(8), 301; https://doi.org/10.3390/batteries11080301 - 6 Aug 2025

Abstract

Amidst the background of accelerated global energy transition, the safety risk of lithium-ion battery energy storage systems, especially the fire hazard, has become a key bottleneck hindering their large-scale application, and there is an urgent need to build a systematic prevention and control [...] Read more.

Amidst the background of accelerated global energy transition, the safety risk of lithium-ion battery energy storage systems, especially the fire hazard, has become a key bottleneck hindering their large-scale application, and there is an urgent need to build a systematic prevention and control program. This paper focuses on the fire characteristics and thermal runaway mechanism of lithium-ion battery energy storage power stations, analyzing the current situation of their risk prevention and control technology across the dimensions of monitoring and early warning technology, thermal management technology, and fire protection technology, and comparing and analyzing the characteristics of each technology from multiple angles. Building on this analysis, this paper summarizes the limitations of the existing technologies and puts forward prospective development paths, including the development of multi-parameter coupled monitoring and warning technology, integrated and intelligent thermal management technology, clean and efficient extinguishing agents, and dynamic fire suppression strategies, aiming to provide solid theoretical support and technical guidance for the precise risk prevention and control of lithium-ion battery storage power stations. Full article

(This article belongs to the Special Issue Advanced Battery Safety Technologies: From Materials to Systems)

► Show Figures

Graphical abstract

16 pages, 2886 KB

Open AccessArticle

Incremental Capacity-Based Variable Capacitor Battery Model for Effective Description of Charge and Discharge Behavior

by Ngoc-Thao Pham, Sungoh Kwon and Sung-Jin Choi

Batteries 2025, 11(8), 300; https://doi.org/10.3390/batteries11080300 - 5 Aug 2025

Abstract

Determining charge and discharge behavior is essential for optimizing charging strategies and evaluating balancing algorithms in battery energy storage systems and electric vehicles. Conventionally, a sequence of circuit simulations or tedious hardware tests is required to evaluate the performance of the balancing algorithm. [...] Read more.

Determining charge and discharge behavior is essential for optimizing charging strategies and evaluating balancing algorithms in battery energy storage systems and electric vehicles. Conventionally, a sequence of circuit simulations or tedious hardware tests is required to evaluate the performance of the balancing algorithm. To mitigate these problems, this paper proposes a variable capacitor model that can be easily built from the incremental capacity curve. This model provides a direct and insightful R-C time constant method for the charge/discharge time calculation. After validating the model accuracy by experimental results based on the cylindrical lithium-ion cell test, a switched-capacitor active balancing and a passive cell balancing circuit are implemented to further verify the effectiveness of the proposed model in calculating the cell balancing time within 2% error. Full article

(This article belongs to the Special Issue Batteries: 10th Anniversary)

► Show Figures

Figure 1

19 pages, 2626 KB

Open AccessArticle

Process–Structure–Property Correlations in Twin-Screw Extrusion of Graphitic Negative Electrode Pastes for Lithium Ion Batteries Focusing on Kneading Concentrations

by Kristina Borzutzki, Markus Börner, Olga Fromm, Uta Rodehorst and Martin Winter

Batteries 2025, 11(8), 299; https://doi.org/10.3390/batteries11080299 - 5 Aug 2025

Abstract

A continuous mixing process with a twin-screw extruder was investigated for graphite-based negative electrode pastes for high-power applications. In the extrusion-based mixing process, the first kneading concentration is one of the key processing parameters for systematic optimization of relevant electrode paste properties like [...] Read more.

A continuous mixing process with a twin-screw extruder was investigated for graphite-based negative electrode pastes for high-power applications. In the extrusion-based mixing process, the first kneading concentration is one of the key processing parameters for systematic optimization of relevant electrode paste properties like viscosity and particle size distribution. For different active materials at a constant electrode paste composition, a clear correlation of increasing kneading concentration with decreasing viscosity can be observed up to a certain reversal point, initiating a change in the trend and the rheological behavior, thus indicating a process limit. The fundamental effects causing this change and the associated impact on materials and battery performance were evaluated by applying further analytical methods and electrochemical characterization. It is revealed that the change in viscosity is associated with enhanced de-agglomeration of the carbon black additive and with partial particle grinding of the active material and thus a partial change in the interlayer distance of graphene layers and, correspondingly, the electrochemical behavior of the active material. Beyond this, correlations between processing parameters and product properties are presented. Furthermore, indicators are suggested with which monitoring of the machine parameters enables the detection of changes in the electrode paste characteristics. Full article

(This article belongs to the Special Issue Batteries: 10th Anniversary)

► Show Figures

Graphical abstract

51 pages, 4099 KB

Open AccessReview

Artificial Intelligence and Digital Twin Technologies for Intelligent Lithium-Ion Battery Management Systems: A Comprehensive Review of State Estimation, Lifecycle Optimization, and Cloud-Edge Integration

by Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Hicham Chaoui, Saad Mekhilef, Shi Xue Dou and Khay See

Batteries 2025, 11(8), 298; https://doi.org/10.3390/batteries11080298 - 5 Aug 2025

Abstract

The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery [...] Read more.

The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery Management Systems (BMS). This review paper explores how artificial intelligence (AI) and digital twin (DT) technologies can be integrated to enable the intelligent BMS of the future. It investigates how powerful data approaches such as deep learning, ensembles, and models that rely on physics improve the accuracy of predicting state of charge (SOC), state of health (SOH), and remaining useful life (RUL). Additionally, the paper reviews progress in AI features for cooling, fast charging, fault detection, and intelligible AI models. Working together, cloud and edge computing technology with DTs means better diagnostics, predictive support, and improved management for any use of EVs, stored energy, and recycling. The review underlines recent successes in AI-driven material research, renewable battery production, and plans for used systems, along with new problems in cybersecurity, combining data and mass rollout. We spotlight important research themes, existing problems, and future drawbacks following careful analysis of different up-to-date approaches and systems. Uniting physical modeling with AI-based analytics on cloud-edge-DT platforms supports the development of tough, intelligent, and ecologically responsible batteries that line up with future mobility and wider use of renewable energy. Full article

(This article belongs to the Special Issue Battery Management and Advanced Energy Storage/Conversion Technologies in Renewable Power Systems: From Batteries to Fuel Cells and Hybrid Solutions)

► Show Figures

Figure 1

Journal Description

Batteries

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Topical Collections

Further Information

Guidelines

MDPI Initiatives

Follow MDPI