Batteries

11 pages, 1796 KB

Open AccessArticle

NVPF Sodium-Ion Versus NMC and LFP Lithium-Ion Batteries in Thermal Runaway: Vent Gas Composition and Thermal Analysis

by Gabriel Ferdigg and Christiane Mair (Essl)

Batteries 2025, 11(9), 323; https://doi.org/10.3390/batteries11090323 - 29 Aug 2025

In this study, cells with three different cell chemistries Na₃V₂(PO₄)₂F₃ (NVPF), LiNi_0.6Mn_0.2Co_0.2O₂ (NMC) and LiFePO₄ (LFP) are analyzed in exactly the same setup to compare the [...] Read more.

In this study, cells with three different cell chemistries Na₃V₂(PO₄)₂F₃ (NVPF), LiNi_0.6Mn_0.2Co_0.2O₂ (NMC) and LiFePO₄ (LFP) are analyzed in exactly the same setup to compare the hazardous vent gases and their thermal behavior during thermal runaway (TR). Additionally, the influence of different triggers on the failure behavior of NVPF cells is elucidated. The innovative perspective is providing a direct comparison of the three cell chemistries, the influence of the trigger method on the vent gas composition and the thermal behavior. Of the three cell chemistries, LFP releases the least amount of vent gas at 0.02 mol/Ah (41% H₂, 27% CO₂, 8% CO), followed by NVPF at 0.05 mol/Ah (42% CO₂, 17% electrolyte solvent, 15% H₂ and 10% CO) and NMC at 0.07 mol/Ah (36% CO, 24% CO₂, 19% H₂). The maximum vent gas temperature increases from NVPF (265 °C) to LFP (446 °C) and NMC (1050 °C). As for the triggers, overcharge has the highest vent gas production of the NVPF cells at 0.07 mol/Ah. The results offer valuable insight into storage system design and expand the assessment of battery cells. Full article

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23 pages, 7024 KB

Open AccessArticle

Aging Estimation and Clustering of Used EV Batteries for Second-Life Applications

by Álvaro Pérez-Borondo, Jon Sagardui-Lacalle and Lucia Gauchia

Batteries 2025, 11(9), 322; https://doi.org/10.3390/batteries11090322 - 28 Aug 2025

Abstract

This study presents an integrated machine learning framework to evaluate the aging states of lithium-ion batteries and to classify them according to their second-life application potential. The methodology combines two key components: a set of regression models to estimate critical health indicators, such [...] Read more.

This study presents an integrated machine learning framework to evaluate the aging states of lithium-ion batteries and to classify them according to their second-life application potential. The methodology combines two key components: a set of regression models to estimate critical health indicators, such as capacity and internal resistance, and a classification stage to group batteries based on these parameters. The proposed models were trained and validated using the NASA Battery Aging Datasets. Through an in-depth analysis of environmental conditions, the study identifies their influence on aging metrics, reinforcing the relevance of the input features selected. Furthermore, a clustering-based approach was employed to validate the classification performance and to reveal the link between a battery’s operation and its aging in the Euclidean space. The results show accurate predictions without signs of overfitting or underfitting, and the classification framework proved robust across the evaluated cases. This suggests that the proposed method can serve as a scalable and adaptable tool to guide battery repurposing strategies. Overall, the findings contribute to bridging the gap between battery diagnostics and real-world energy storage applications, offering practical insights to optimize second-life deployment. Full article

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13 pages, 2288 KB

Open AccessArticle

State-of-Health Estimation of LiFePO₄ Batteries via High-Frequency EIS and Feature-Optimized Random Forests

by Zhihan Yan, Xueyuan Wang, Xuezhe Wei, Haifeng Dai and Lifang Liu

Batteries 2025, 11(9), 321; https://doi.org/10.3390/batteries11090321 - 28 Aug 2025

Abstract

Accurate state-of-health (SOH) estimation of lithium iron phosphate (LiFePO₄) batteries is critical for ensuring the safety and performance of electric vehicles, particularly under extreme operating conditions. This study presents a data-driven SOH prediction framework based on high-frequency electrochemical impedance spectroscopy (EIS) [...] Read more.

Accurate state-of-health (SOH) estimation of lithium iron phosphate (LiFePO₄) batteries is critical for ensuring the safety and performance of electric vehicles, particularly under extreme operating conditions. This study presents a data-driven SOH prediction framework based on high-frequency electrochemical impedance spectroscopy (EIS) measurements conducted at −5 °C across various states of charge (SOCs). Feature parameters were extracted from the impedance spectra using equivalent circuit modeling. These features were optimized through Bayesian weighting and subsequently fed into three machine learning models: Random Forest (RF), Gradient Boosting (GB), and Extreme Gradient Boosting (XGB). To mitigate SOC-dependent variations, the models were trained, validated, and tested using features from different SOC levels for each aging cycle. This work provides a practical and interpretable approach for battery health monitoring using high-frequency EIS data, even under sub-zero temperature and partial-SOC conditions. The findings offer valuable insights for developing SOC-agnostic SOH estimation models, advancing the reliability of battery management systems in real-world applications. Full article

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17 pages, 3686 KB

Open AccessArticle

The Effects of Cell Chemistry, State of Charge, and Abuse Method on Gas Generation in Li-ion Cell Failure

by Gemma E. Howard, Jonathan E. H. Buston, Jason Gill, Steven L. Goddard, Jack W. Mellor and Philip A. P. Reeve

Batteries 2025, 11(9), 320; https://doi.org/10.3390/batteries11090320 - 27 Aug 2025

Abstract

We report on the effect state of charge (SoC), cell format, and chemistry have on the volume and composition (H₂, CO₂, CO, CH₄, C₂H₄, C₂H₆, C₃H₆ [...] Read more.

We report on the effect state of charge (SoC), cell format, and chemistry have on the volume and composition (H₂, CO₂, CO, CH₄, C₂H₄, C₂H₆, C₃H₆, and C₃H₈) of cell failure gas from Li-ion cells. Nickel manganese cobalt oxide (NMC) 21700 cells with a 5 Ah capacity were externally heated to failure at a 5–100% SoC under an inert atmosphere. This showed that the volume of gas increased with cell SoC (1.8 L at 5% SoC vs. 8.3 L at 100% SoC). The effect of the cell chemistry format and abuse method was also investigated using 18650, pouch, and prismatic cells (2.3–50 Ah) with Ni-based or lithium cobalt oxide (LCO) cathodes or lithium titanium oxide (LTO) anodes. The results showed that at higher SoCs, larger quantities of gas were generated; however, there was no correlation between the cell SoC and the composition of gases produced. Tests on the other cells found that the Ni-based cell generated 1.29–1.89 L/Ah of gas. The main constituents of this were H₂, CO, and CO₂; however, all other hydrocarbons were identified in varying quantities. The LTO cells generated lower volumes of gas, 0.8 L/Ah compared to Ni-based cells, and the gas was found to contain lower H₂ concentrations but higher concentrations of CO₂. The LCO cell was found to generate a gas volume of 1.2 L/Ah. This forms the final of four papers which cover a total of 213 tests on 29 cell types with six different chemistries, all tested using a single robust testing method. Full article

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24 pages, 6368 KB

Open AccessArticle

Electro-Thermal Modeling and Parameter Identification of an EV Battery Pack Using Drive Cycle Data

by Vinura Mannapperuma, Lalith Chandra Gaddala, Ruixin Zheng, Doohyun Kim, Youngki Kim, Ankith Ullal, Shengrong Zhu and Kyoung Pyo Ha

Batteries 2025, 11(9), 319; https://doi.org/10.3390/batteries11090319 - 27 Aug 2025

Abstract

This paper presents a novel electro-thermal modeling approach for a lithium-ion battery pack in an electric vehicle (EV), along with parameter identification using controller area network (CAN) data collected from chassis dynamometer and real-world driving tests. The proposed electro-thermal model consists of a [...] Read more.

This paper presents a novel electro-thermal modeling approach for a lithium-ion battery pack in an electric vehicle (EV), along with parameter identification using controller area network (CAN) data collected from chassis dynamometer and real-world driving tests. The proposed electro-thermal model consists of a first-order equivalent circuit model (ECM) and a lumped-parameter thermal network in considering a simplified cooling circuit layout and temperature distributions across four distinct zones within the battery pack. This model captures the nonuniform heat transfer between the pack modules and the coolant, as well as variations in coolant temperature and flow rates. Model parameters are identified directly from vehicle-level test data without relying on laboratory-level measurements. Validation results demonstrate that the model can predict terminal voltage with an RMSE of less than 6 V (normalized root mean square error of less than 2%), and battery module surface temperatures with root mean square errors of less than 2 °C for over 90% of the test cases. The proposed approach provides a cost-effective and accurate solution for predicting electro-thermal behavior of EV battery systems, making it a valuable tool for battery design and management to optimize performance and ensure the safety of EVs. Full article

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

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22 pages, 8525 KB

Open AccessReview

Protein-Based Strategies for Non-Alkali Metal-Ion Batteries

by Qian Wang, Chenxu Wang and Wei-Hong Zhong

Batteries 2025, 11(9), 318; https://doi.org/10.3390/batteries11090318 - 26 Aug 2025

Abstract

Batteries are a cornerstone of modern technology that supports a wide range of applications including portable electronics, electric vehicles and large-scale energy storage for renewable power systems. Despite their widespread use, commercial Li-ion batteries are limited by the mineral resources of Li. The [...] Read more.

Batteries are a cornerstone of modern technology that supports a wide range of applications including portable electronics, electric vehicles and large-scale energy storage for renewable power systems. Despite their widespread use, commercial Li-ion batteries are limited by the mineral resources of Li. The rapidly growing battery market demands alternative battery systems, such as non-alkali metal-ion batteries, that are capable of delivering comparative energy densities. In the meantime, improving the performance of the batteries via generating sustainable strategies has been broadly studied. Proteins, as re naturally evolved macromolecules that possess diverse structures and functional groups, have been demonstrated to be able to transport various metallic ions inside bio-organisms. Therefore, active studies have been carried out on the use of natural proteins (e.g., zein, soy, fibroin, bovine serum albumin, etc.) to enhance the electrochemical performance of non-alkali metal-ion batteries. This review provides a comprehensive summary of recent advances on the studies of protein-based strategies for non-alkali metal-ion batteries and outlines perspectives for future sustainable electrochemical energy storage systems. Full article

(This article belongs to the Special Issue Sustainable Materials and Recycling Processes for Battery Production)

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37 pages, 5256 KB

Open AccessReview

Carbon/High-Entropy Alloy Nanocomposites: Synergistic Innovations and Breakthrough Challenges for Electrochemical Energy Storage

by Li Sun, Hangyu Li, Yu Dong, Wan Rong, Na Zhou, Rui Dang, Jianle Xu, Qigao Cao and Chunxu Pan

Batteries 2025, 11(9), 317; https://doi.org/10.3390/batteries11090317 - 23 Aug 2025

Abstract

Against the backdrop of accelerating global energy transition, developing high-performance energy-storage systems is crucial for achieving carbon neutrality. Traditional electrode materials are limited by a single densification storage mechanism and low conductivity, struggling to meet demands for high energy/power density and a long [...] Read more.

Against the backdrop of accelerating global energy transition, developing high-performance energy-storage systems is crucial for achieving carbon neutrality. Traditional electrode materials are limited by a single densification storage mechanism and low conductivity, struggling to meet demands for high energy/power density and a long cycle life. Carbon/high-entropy alloy nanocomposites provide an innovative solution through multi-component synergistic effects and cross-scale structural design: the “cocktail effect” of high-entropy alloys confers excellent redox activity and structural stability, while the three-dimensional conductive network of the carbon skeleton enhances charge transfer efficiency. Together, they achieve synergistic enhancement via interfacial electron coupling, stress buffering, and dual storage mechanisms. This review systematically analyzes the charge storage/attenuation mechanisms and performance advantages of this composite material in diverse energy-storage devices (lithium-ion batteries, lithium-sulfur batteries, etc.), evaluates the characteristics and limitations of preparation techniques such as mechanical alloying and chemical vapor deposition, identifies five major challenges (including complex and costly synthesis, ambiguous interfacial interaction mechanisms, lagging theoretical research, performance-cost trade-offs, and slow industrialization processes), and prospectively proposes eight research directions (including multi-scale structural regulation and sustainable preparation technologies, etc.). Through interdisciplinary perspectives, this review aims to provide a theoretical foundation for deepening the understanding of carbon/high-entropy alloy composite energy-storage mechanisms and guiding industrial applications, thereby advancing breakthroughs in electrochemical energy-storage technology under the energy transition. Full article

(This article belongs to the Special Issue Advanced Carbon-Based Materials for Next-Generation Batteries and Supercapacitors)

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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

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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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)

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