Batteries

8 pages, 2056 KiB

Open AccessArticle

A Modified Acrylic Binder Used for the Graphite Negative Electrode in LithiumIon Batteries

by Lianxiang Feng, Wenting Chen, Feng Hai, Xin Gao, Yuyu Ban, Weicheng Xue, Wentao Yan, Yunxiao Yang and Mingtao Li

Batteries 2025, 11(5), 190; https://doi.org/10.3390/batteries11050190 - 13 May 2025

Abstract

The water-based binder has the advantages of non-toxic, non-flammable, small odor, and no pollution to the environment. However, there are problems such as low bond strength and poor battery cycle life of commonly used binders on the market. In this paper, the acrylic [...] Read more.

The water-based binder has the advantages of non-toxic, non-flammable, small odor, and no pollution to the environment. However, there are problems such as low bond strength and poor battery cycle life of commonly used binders on the market. In this paper, the acrylic binder is modified. In addition, acrylic acid/methacrylic acid, acrylonitrile, and octadecyl acrylate/octadecyl methacrylate are copolymerized at high temperature, and a new binder for graphite anode is successfully developed. The binder can significantly improve the affinity between the graphite anode and the electrolyte and the integrity of the graphite particles during the cycle, so that the battery has better electrochemical performance. During the charge and discharge cycle of 1 C, the graphite anode coated with PAANa as a binder was able to cycle 360 cycles and remain stable, which is far better than the 192 cycles of the commercial binder LA133. It is proved that the experimental formula has a certain commercial application prospect. Full article

(This article belongs to the Special Issue Functional Binders and Additives for Rechargeable Batteries)

11 pages, 15871 KiB

Open AccessArticle

Low-Cost, Sustainable Hybrid Aqueous Zinc Metal Batteries Using Ethyl Cellulose as a Binder

by Pedro Pablo Machado Pico, Stefano Colonna and Fabio Ronci

Batteries 2025, 11(5), 189; https://doi.org/10.3390/batteries11050189 - 11 May 2025

Viewed by 171

Abstract

Despite their inherently lower energy density than lithium-ion batteries (LIBs), aqueous zinc metal batteries (AZMBs) have recently attracted interest as rechargeable energy storage devices due to their low cost and high operational and environmental safety. They are composed of metallic zinc as the [...] Read more.

Despite their inherently lower energy density than lithium-ion batteries (LIBs), aqueous zinc metal batteries (AZMBs) have recently attracted interest as rechargeable energy storage devices due to their low cost and high operational and environmental safety. They are composed of metallic zinc as the anode, an aqueous zinc salt electrolyte and a cathode capable of (de)intercalating Zn²⁺ ions upon its (oxidation) reduction reaction. In this work, we studied a hybrid AZMB in which a dual-ion electrolyte containing both Zn²⁺ and Li⁺ ions was used in conjunction with a Li⁺ ion intercalation cathode, i.e., LiFePO₄ (LFP), one of the most common, reliable, and cheap cathodes for LIBs. In this study, we present evidence that, thanks to its insolubility in water, ethyl cellulose (EC) can be effectively utilized as a binder for cathode membranes in AZMBs. Furthermore, its solubility in alcohol provides a significant advantage in avoiding the use of toxic solvents, contributing to a safer and more environmentally friendly approach to the formulation process. Full article

(This article belongs to the Special Issue Development, Application, and Characterization of New Electrode Materials for Advanced Batteries)

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19 pages, 3126 KiB

Open AccessArticle

Multiband Multisine Excitation Signal for Online Impedance Spectroscopy of Battery Cells

by Roberta Ramilli, Nicola Lowenthal, Marco Crescentini and Pier Andrea Traverso

Batteries 2025, 11(5), 188; https://doi.org/10.3390/batteries11050188 - 10 May 2025

Viewed by 150

Abstract

Multisine electrochemical impedance spectroscopy (EIS) represents a highly promising technique for the online characterization of battery functional states, offering the potential to monitor, in real-time, key degradation phenomena such as aging, internal resistance variation, and state of health (SoH) evolution. However, its widespread [...] Read more.

Multisine electrochemical impedance spectroscopy (EIS) represents a highly promising technique for the online characterization of battery functional states, offering the potential to monitor, in real-time, key degradation phenomena such as aging, internal resistance variation, and state of health (SoH) evolution. However, its widespread adoption in embedded systems is currently limited by the need to balance measurement accuracy with strict energy constraints and the requirement for short acquisition times. This work proposes a novel broadband EIS approach based on a multiband multisine excitation strategy in which the excitation signal spectrum is divided into multiple sub-bands that are sequentially explored. This enables the available energy to be concentrated on a limited portion of the spectrum at a time, thereby significantly improving the signal-to-noise ratio (SNR) without substantially increasing the total measurement time. The result is a more energy-efficient method that maintains high diagnostic precision. We further investigated the optimal design of these multiband multisine sequences, taking into account realistic constraints imposed by the sensing hardware such as limitations in excitation amplitude and noise level. The effectiveness of the proposed method was demonstrated within a comprehensive simulation framework implementing a complete impedance measurement system. Compared with conventional excitation techniques (i.e., the sine sweep and the classical single-band multisine methods), the proposed strategy is an optimal trade-off solution both in terms of energy efficiency and measurement time. Therefore, the technique is a valuable solution for real-time, embedded, and in situ battery diagnostics, with direct implications for the development of intelligent battery management systems (BMS), predictive maintenance, and enhanced safety in energy storage applications. Full article

(This article belongs to the Special Issue Recent Advances in Battery Measurement and Management Systems)

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11 pages, 6157 KiB

Open AccessArticle

Numerical Study of the Effects of Heat Loss and Solid Thermal Conductivity on Syngas Production for Fuel Cells

by Xiaolong Wang, Mengmeng Yu, Zunmin Li, Zhen Wang, Xiuxia Zhang, Junrui Shi, Xiangjin Kong and Jinsheng Lv

Batteries 2025, 11(5), 187; https://doi.org/10.3390/batteries11050187 - 9 May 2025

Viewed by 191

Abstract

Syngas can be used as feedstock for efficient energy conversion in solid oxide fuel cells (SOFCs). In the current paper, the conversion efficiency of methane to synthesis gas (H₂ and CO) within a two-layer porous media reactor is investigated by a one-dimensional [...] Read more.

Syngas can be used as feedstock for efficient energy conversion in solid oxide fuel cells (SOFCs). In the current paper, the conversion efficiency of methane to synthesis gas (H₂ and CO) within a two-layer porous media reactor is investigated by a one-dimensional two-temperature model. A detailed chemical reaction mechanism GRI-Mech 1.2 is used to describe the chemical processes. Attention is focused on CO₂ content in the methane/air mixture, heat loss to the surroundings, and solid thermal conductivity on temperature distribution and conversion efficiency. Numerical results show that addition of CO₂ to the methane/air mixture improves the conversion efficiency. For a molar ratio of CO₂/CH₄ = 1, the conversion efficiency reaches 44.8%. An increase in heat loss to the surroundings leads to a decrease in conversion efficiency. A greater solid thermal conductivity can improve the conversion efficiency. Full article

(This article belongs to the Special Issue Challenges, Progress, and Outlook of High-Performance Fuel Cells)

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14 pages, 3257 KiB

Open AccessArticle

Enhanced OCV Estimation in LiFePO4 Batteries: A Novel Statistical Approach Leveraging Real-Time Knee/Elbow Detection

by Teodor-Iulian Voicila, Bogdan-Adrian Enache, Vasilis Argyriou, Panagiotis Sarigiannidis, Mihai-Alexandru Pisla and George-Calin Seritan

Batteries 2025, 11(5), 186; https://doi.org/10.3390/batteries11050186 - 8 May 2025

Viewed by 176

Abstract

The rapid advancement of electric vehicles (EVs) and renewable energy storage systems has significantly increased the demand for reliable and efficient battery technologies. Lithium iron phosphate (LFP) batteries are particularly suitable for these applications due to their superior thermal stability and long cycle [...] Read more.

The rapid advancement of electric vehicles (EVs) and renewable energy storage systems has significantly increased the demand for reliable and efficient battery technologies. Lithium iron phosphate (LFP) batteries are particularly suitable for these applications due to their superior thermal stability and long cycle life. A critical parameter in optimizing the performance of LFP batteries is the open-circuit voltage (OCV), essential for accurate state of charge (SoC) estimation. The accurate determination of the OCV is challenging due to relaxation effects post-charging/discharging, causing voltage changes for up to 24 h or even more until stabilization. This paper presents a novel statistical model for OCV estimation that employs an online observer to detect the knee/elbow point in the voltage relaxation curve. By utilizing the voltage at the knee/elbow point and the initial voltage, the model accurately computes the OCV at the stabilization point. The proposed method, validated with extensive experimental data, achieves high accuracy, with a computed error of less than 0.26% for charging and under 1.2% for discharging. Full article

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64 pages, 6751 KiB

Open AccessReview

Powering the Future Smart Mobility: A European Perspective on Battery Storage

by Natascia Andrenacci, Francesco Vitiello, Chiara Boccaletti and Francesco Vellucci

Batteries 2025, 11(5), 185; https://doi.org/10.3390/batteries11050185 - 7 May 2025

Viewed by 128

Abstract

Batteries are central to the global energy system and fundamental elements for energy transition and future mobility. In particular, the growth in electric vehicle (EV) sales is pushing up demand for batteries. Most of the battery demand for EVs today can be met [...] Read more.

Batteries are central to the global energy system and fundamental elements for energy transition and future mobility. In particular, the growth in electric vehicle (EV) sales is pushing up demand for batteries. Most of the battery demand for EVs today can be met with domestic or regional production in China, while the share of imports remains relatively large in Europe and the United States. Boosting the industrial base for battery production is therefore a key task for the EU. To make its battery supply chains secure, resilient, and sustainable, the EU’s approach consists of improving cooperation among stakeholders, providing the sector with funding, and establishing a comprehensive regulatory framework. In this paper, an accurate review of the state-of-the-art of automotive batteries is provided, including the performance, safety, sustainability, and costs of the different battery technologies. The significant challenges the EU battery sector must face, such as dependencies on third countries and high energy and labor costs, are discussed. An overview of the present European regulation and of future trends is provided. Full article

(This article belongs to the Special Issue Towards a Smarter Battery Management System: 2nd Edition)

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13 pages, 2869 KiB

Open AccessArticle

Study on Thermal Behavior and Safety Properties of Na₄Fe₃(PO₄)₂(P₂O₇) and NaNi_1/3Fe_1/3Mn_1/3O₂ Cathode-Based Sodium Ion Battery

by Ran Yu, Shiyang Liu, Xuehai Li, Bin Wei and Xiaochao Wu

Batteries 2025, 11(5), 184; https://doi.org/10.3390/batteries11050184 - 7 May 2025

Viewed by 94

Abstract

Sodium-ion batteries (SIBs) share similar working principles with lithium-ion batteries while demonstrating cost advantages. However, the current understanding of their safety characteristics remains insufficient, and the thermal runaway mechanisms of different SIB systems have not been fully elucidated. This study investigated the following [...] Read more.

Sodium-ion batteries (SIBs) share similar working principles with lithium-ion batteries while demonstrating cost advantages. However, the current understanding of their safety characteristics remains insufficient, and the thermal runaway mechanisms of different SIB systems have not been fully elucidated. This study investigated the following two mainstream sodium-ion battery systems: polyanion-type compound (PAC) and layered transition metal oxide (TMO) cathodes. Differential scanning calorimetry (DSC) was employed to evaluate the thermal stability of cathodes and anodes, examining the effects of state of charge (SOC), cycling, and overcharging on electrode thermal stability. The thermal stability of electrolytes with different compositions was also characterized and analyzed. Additionally, adiabatic thermal runaway tests were conducted using an accelerating rate calorimeter (ARC) to explore temperature–voltage evolution patterns and temperature rise rates. The study systematically investigated heat-generating reactions during various thermal runaway stages and conducted a comparative analysis of the thermal runaway characteristics between these two battery systems. Full article

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

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14 pages, 4014 KiB

Open AccessArticle

SOH Estimation of Lithium-Ion Batteries Using Distribution of Relaxation Times Parameters and Long Short-Term Memory Model

by Abdul Shakoor Akram, Muhammad Sohaib and Woojin Choi

Batteries 2025, 11(5), 183; https://doi.org/10.3390/batteries11050183 - 7 May 2025

Viewed by 109

Abstract

Lithium-ion batteries are extensively utilized in modern applications due to their high energy density, long cycle life, and efficiency. With the increasing demand for sustainable energy storage solutions, accurately estimating the State of Health (SOH) is essential to address challenges related to battery [...] Read more.

Lithium-ion batteries are extensively utilized in modern applications due to their high energy density, long cycle life, and efficiency. With the increasing demand for sustainable energy storage solutions, accurately estimating the State of Health (SOH) is essential to address challenges related to battery degradation and secondary life management. Electrochemical Impedance Spectroscopy (EIS) is a widely used diagnostic tool for evaluating battery performance due to its simplicity and cost-effectiveness. However, EIS often struggles to decouple overlapping electrochemical processes. The Distribution of Relaxation Times (DRT) method has emerged as a powerful alternative, enabling the isolation of key processes, such as ohmic resistance, SEI resistance, charge transfer resistance, and diffusion, thereby providing deeper insights into battery aging mechanisms. This paper presents a novel approach for estimating the State of Health (SOH) of batteries by leveraging DRT parameters across multiple State of Charge (SOC) levels. This study incorporates data from three lithium-ion batteries, each with distinct initial capacities, introducing variability that reflects the natural differences observed in real-world battery performance. By employing a Long Short-Term Memory (LSTM)-based machine learning model, the proposed framework demonstrates a superior accuracy in SOH prediction compared to traditional EIS-based methods. The results highlight the sensitivity of DRT parameters to SOH degradation and validate their effectiveness as reliable indicators for battery health. This research underscores the potential of combining a DRT analysis with AI-driven models to advance scalable, precise, and interpretable battery diagnostics. Full article

(This article belongs to the Special Issue Towards a Smarter Battery Management System: 2nd Edition)

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16 pages, 951 KiB

Open AccessFeature PaperArticle

A Water-Based Fire-Extinguishing Agent of Lithium Iron Phosphate Battery Fire via an Analytic Hierarchy Process-Fuzzy TOPSIS Decision-Marking Method

by Shuai Yuan, Kuo Wang, Feng Tai, Donghao Cheng, Qi Zhang, Yujie Cui, Xinming Qian, Chunwen Sun, Song Liu and Xin Chen

Batteries 2025, 11(5), 182; https://doi.org/10.3390/batteries11050182 - 2 May 2025

Viewed by 187

Abstract

It is well known that the safety concerns surrounding lithium-ion batteries (LIBs), such as fire and explosion, are currently a bottleneck problem for the large-scale usage of energy storage power stations. The study of water-based fire-extinguishing agents used for LIBs is a promising [...] Read more.

It is well known that the safety concerns surrounding lithium-ion batteries (LIBs), such as fire and explosion, are currently a bottleneck problem for the large-scale usage of energy storage power stations. The study of water-based fire-extinguishing agents used for LIBs is a promising direction. How to choose a suitable water-based fire-extinguishing agent is a significant scientific problem. In this study, a comprehensive evaluation model, including four primary indexes and eleven secondary indexes was established, which was used in the scenario of an electrochemical energy storage power station. The model is only suitable for assessing water-based fire extinguishing for suppressing lithium iron phosphate battery fire. Based on the comprehensive evaluation index system and extinguishing experiment data, the analytic hierarchy process (AHP) combined with fuzzy TOPSIS was used to evaluate the performances of the three kinds of water-based fire-extinguishing agents. According to the results of the fuzzy binary contrast method, the three kinds of fire-extinguishing agents could be ranked as follows: YS1000 > F-500 additive > pure water. The study provided a method for choosing and preparing a suitable fire-extinguishing agent for lithium iron phosphate batteries. Full article

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34 pages, 11293 KiB

Open AccessReview

Recent Advances in the Application of MOFs in Supercapacitors

by Christos Argirusis, Maria-Eleni Katsanou, Niyaz Alizadeh, Nikolaos Argirusis and Georgia Sourkouni

Batteries 2025, 11(5), 181; https://doi.org/10.3390/batteries11050181 - 2 May 2025

Viewed by 328

Abstract

As the need for energy is constantly increasing and in the long term fossil fuels are not an option because of global overheating due to the greenhouse effect, alternative energy production concepts such as photovoltaics, wind energy, IR energy harvesters etc., have been [...] Read more.

As the need for energy is constantly increasing and in the long term fossil fuels are not an option because of global overheating due to the greenhouse effect, alternative energy production concepts such as photovoltaics, wind energy, IR energy harvesters etc., have been developed. The problem is that renewable energy sources are stochastic, and therefore there is a need for electrical energy storage either in rechargeable batteries or in high-performance supercapacitors. In this respect, novel materials are needed to meet the challenges that are related to these technologies. Metal–organic frameworks (MOFs) represent highly promising materials for energy storage applications in supercapacitors (SCs) and thus in recent years have become essential for clean and efficient energy conversion and storage. Metal–organic frameworks (MOFs) present numerous benefits as electrocatalysts, electrolyte membranes, and fuel storage materials; they exhibit exceptional design versatility, extensive surface-to-volume ratios, and permit functionalization with multivalent ligands and metal centers. Here we present an overview of MOF-based materials for electrical energy storage using high-performance supercapacitors. This review deals with recent advances in MOF-based materials for supercapacitors. Finally, an outlook on the future use and restrictions of MOFs in electrochemical applications, with focus on supercapacitors, is given. Full article

(This article belongs to the Special Issue High-Performance Supercapacitors: Advancements & Challenges)

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22 pages, 3660 KiB

Open AccessArticle

A Multi-Encoder BHTP Autoencoder for Robust Lithium Battery SOH Prediction Under Small-Sample Scenarios

by Chang Liu, Shunli Wang, Zhiqiang Ma, Siyuan Guo and Yixiong Qin

Batteries 2025, 11(5), 180; https://doi.org/10.3390/batteries11050180 - 2 May 2025

Viewed by 197

Abstract

Accurate prediction of the state of health (SOH) in lithium batteries (LiBs) is essential for ensuring operational safety, extending battery lifespan, and enabling effective second-life applications. However, achieving precise SOH prediction under small-sample conditions remains a significant challenge due to inherent variability among [...] Read more.

Accurate prediction of the state of health (SOH) in lithium batteries (LiBs) is essential for ensuring operational safety, extending battery lifespan, and enabling effective second-life applications. However, achieving precise SOH prediction under small-sample conditions remains a significant challenge due to inherent variability among battery cells and capacity recovery phenomena, which result in irregular degradation patterns and hinder effective feature extraction. To overcome these challenges, this study introduces an advanced autoencoder-based method specifically designed for SOH prediction in small-sample scenarios. This method employs a multi-encoder structure—comprising token, positional, and temporal encoders—to comprehensively capture the multi-dimensional characteristics of SOH sequences. Furthermore, a BHTP module is integrated to facilitate feature fusion and enhance the model’s stability and interpretability. By utilizing a pre-training and fine-tuning strategy, the proposed method effectively reduces computational complexity and the number of model parameters while maintaining high prediction accuracy. The validation of the NASA 18650 lithium cobalt oxide battery dataset under various discharge strategies shows that the proposed method achieves fast convergence and outperforms traditional prediction methods. Compared with other models, our method reduces the RMSE by 0.004 and the MAE by 0.003 on average. In addition, ablation experiments show that the addition of the multi-encoder structure and the BHTP module improves the RMSE and MAE by 0.008 and 0.007 on average, respectively. These results highlight the robustness and utility of the proposed method in real battery management systems, especially under data-scarce conditions. Full article

(This article belongs to the Special Issue Modeling, Reliability and Health Management of Lithium-Ion Batteries—2nd Edition)

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52 pages, 1276 KiB

Open AccessReview

A Review of Battery Energy Storage Optimization in the Built Environment

by Simone Coccato, Khadija Barhmi, Ioannis Lampropoulos, Sara Golroodbari and Wilfried van Sark

Batteries 2025, 11(5), 179; https://doi.org/10.3390/batteries11050179 - 2 May 2025

Viewed by 682

Abstract

The increasing adoption of renewable energy sources necessitates efficient energy storage solutions, with buildings emerging as critical nodes in residential energy systems. This review synthesizes state-of-the-art research on the role of batteries in residential settings, emphasizing their diverse applications, such as energy storage [...] Read more.

The increasing adoption of renewable energy sources necessitates efficient energy storage solutions, with buildings emerging as critical nodes in residential energy systems. This review synthesizes state-of-the-art research on the role of batteries in residential settings, emphasizing their diverse applications, such as energy storage for photovoltaic systems, peak shaving, load shifting, demand response, and backup power. Distinct from prior review studies, our work provides a structured framework categorizing battery applications, spanning individual use, shared systems, and energy communities, and examines modeling techniques like State of Charge estimation and degradation analysis. Highlighting the integration of batteries with renewable infrastructures, we explore multi-objective optimization strategies and hierarchical decomposition methods for effective battery utilization. The findings underscore that advanced battery management systems and technological innovations are aimed at extending battery life and enhancing efficiency. Finally, we identify critical knowledge gaps and propose directions for future research, with a focus on scaling battery applications to meet operational, economic, and environmental objectives. By bridging theoretical insights with practical applications, this review contributes to advancing the understanding and optimization of residential energy storage systems within the energy transition. Full article

(This article belongs to the Section Battery Modelling, Simulation, Management and Application)

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25 pages, 3739 KiB

Open AccessArticle

Electrochemical–Thermal Modeling of Lithium-Ion Batteries: An Analysis of Thermal Runaway with Observation on Aging Effects

by Milad Tulabi and Roberto Bubbico

Batteries 2025, 11(5), 178; https://doi.org/10.3390/batteries11050178 - 2 May 2025

Viewed by 398

Abstract

The increasing demand for energy storage solutions, particularly in electric vehicles and renewable energy systems, has intensified research on lithium-ion (Li-ion) battery safety and performance. A critical challenge is thermal runaway (TR), a highly exothermic sequence of reactions triggered by mechanical, electrical, or [...] Read more.

The increasing demand for energy storage solutions, particularly in electric vehicles and renewable energy systems, has intensified research on lithium-ion (Li-ion) battery safety and performance. A critical challenge is thermal runaway (TR), a highly exothermic sequence of reactions triggered by mechanical, electrical, or thermal abuse, which can lead to catastrophic failures. While most TR models focus on fresh cells, aging significantly impacts battery behavior and safety. This study develops an electrochemical–thermal coupled model that incorporates aging effects to better predict thermal behavior and TR initiation in cylindrical Li-ion batteries. The model is validated against experimental data for fresh NMC and aged NCA cells, and statistical analysis is conducted to identify key factors influencing TR (p < 0.05). A full factorial design evaluates the effects of internal resistance (10, 20, 30, and 40 mΩ), capacity (1, 2, 3, and 5 Ah), and current rate (1C, 3C, 6C, and 8C) on temperature evolution. Additionally, a machine learning algorithm (logistic regression) is employed to identify an internal resistance threshold, beyond which thermal runaway (TR) becomes highly probable, and to predict TR probability based on key battery parameters. The model achieved a high prediction accuracy of 95% on the test dataset. Results indicate that aging affects thermal stability in complex ways. The increased internal resistance exacerbates heating rates, while capacity fade reduces stored energy, mitigating TR risk. These findings provide a validated framework for enhancing battery thermal management and predictive safety mechanisms, which contributed to the development of safer, more reliable Li-ion energy storage systems. Full article

(This article belongs to the Special Issue The Breakthrough of Traditional Electrochemical Energy Storage Systems)

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27 pages, 7012 KiB

Open AccessArticle

Molten Salt Electrolyte for Na-ZnCl₂ All-Liquid Battery for Grid Storage

by Wenjin Ding, Ralf Hoffmann, Akshata Barge, Ole S. Kjos, Norbert Weber, Tom Weier and Thomas Bauer

Batteries 2025, 11(5), 177; https://doi.org/10.3390/batteries11050177 - 1 May 2025

Viewed by 213

Abstract

Zeolite Battery Research Africa (ZEBRA) batteries (Na-NiCl₂ solid electrolyte batteries, SEBs) have commercial applications in energy storage due to their low costs and recyclability, long lifetime, and high safety. In commercial ZEBRA batteries, Ni electrode and beta’’-alumina solid electrolyte (BASE) have a [...] Read more.

Zeolite Battery Research Africa (ZEBRA) batteries (Na-NiCl₂ solid electrolyte batteries, SEBs) have commercial applications in energy storage due to their low costs and recyclability, long lifetime, and high safety. In commercial ZEBRA batteries, Ni electrode and beta’’-alumina solid electrolyte (BASE) have a more than 70% share of the overall cell material costs. Na-ZnCl₂ all-liquid batteries (ALBs), which replace Ni with abundant and low-cost Zn and BASE electrolyte with molten salt electrolyte, could reduce costs and provide a longer lifetime and higher safety, making their application in grid storage promising. However, compared to SEBs, ALBs are in an early development stage, particularly for their molten salt electrolytes, which have a significant effect on the battery performance. Physical and chemical properties of the salt electrolyte like melting temperatures and solubilities of electrode materials (i.e., Na and Zn metal) are vital for the molten salt electrolyte selection and battery cell design and optimization. In this work, the binary and ternary phase diagrams of salt mixtures containing NaCl, CaCl₂, BaCl₂, SrCl₂, and KCl, obtained via FactSage simulation and DSC measurements, as well as the solubilities of electrode materials (Na and Zn metals), are presented and used for the selection of the molten salt electrolyte. Moreover, various criteria, considered for the selection of the molten salt electrolyte, include high electromotive force (EMF) for suitable electrochemical properties, low melting temperature for large charge/discharge range, low solubilities of electrode materials for low self-discharge, low material costs, and high material abundance for easy scale-up. Based on these criteria, the NaCl-CaCl₂-BaCl₂ and NaCl-SrCl₂-KCl salt mixtures are selected as the two most promising ALB molten salt electrolytes and suggested to be tested in the ALB demonstrators currently under development. Full article

(This article belongs to the Special Issue Electrode Materials and Electrolyte for Rechargeable Batteries)

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16 pages, 1987 KiB

Open AccessPerspective

A Perspective on the Challenges and Prospects of Realizing the Second Life of Retired EV Batteries

by Prodip K. Das

Batteries 2025, 11(5), 176; https://doi.org/10.3390/batteries11050176 - 28 Apr 2025

Viewed by 409

Abstract

As electric vehicle (EV) adoption continues to surge globally, the question of what to do with retired EV batteries looms large. While these batteries may no longer meet the rigorous demands of automotive use, they often retain a significant portion of their capacity [...] Read more.

As electric vehicle (EV) adoption continues to surge globally, the question of what to do with retired EV batteries looms large. While these batteries may no longer meet the rigorous demands of automotive use, they often retain a significant portion of their capacity and functionality. This has led to growing interest in exploring second-life applications for retired EV batteries, ranging from stationary energy storage to grid stabilization and beyond. However, numerous challenges must be addressed to unlock the full potential of this emerging sector. This paper delves into the key challenges and prospects associated with the second life of retired EV batteries. It examines technical hurdles, such as battery degradation, safety concerns, and the development of efficient repurposing methods, along with regulatory and economic barriers, including standards for battery reuse, recycling infrastructure, and market dynamics. Additionally, it highlights the potential environmental benefits, including reduced carbon emissions and resource conservation. In conclusion, the second life of retired EV batteries presents both challenges and opportunities. Addressing technical, regulatory, and economic barriers will be essential for realizing the full potential of this growing sector. However, with continued innovation and collaboration across industries, the future looks bright for leveraging retired EV batteries to create a more sustainable energy ecosystem. Full article

(This article belongs to the Special Issue 10th Anniversary of Batteries: Second-Life Applications and Recycling of Li-Ion Batteries)

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19 pages, 4869 KiB

Open AccessArticle

New BMS Topology with Active Cell Balancing Between Electric Vehicles’ Traction and Auxiliary Batteries

by José Gabriel O. Pinto, Manuel Freitas Silva, Luis A. M. Barros and José A. Afonso

Batteries 2025, 11(5), 175; https://doi.org/10.3390/batteries11050175 - 27 Apr 2025

Viewed by 291

Abstract

This paper proposes a new topology for a battery management system (BMS) with active cell balancing capable of exchanging energy between an electric vehicle’s traction and auxiliary batteries. This topology facilitates energy exchange between any cell in the traction battery pack and with [...] Read more.

This paper proposes a new topology for a battery management system (BMS) with active cell balancing capable of exchanging energy between an electric vehicle’s traction and auxiliary batteries. This topology facilitates energy exchange between any cell in the traction battery pack and with the auxiliary battery. The proposed topology allows both the selection of the cells involved in the balancing process and the charging of the auxiliary battery, eliminating the need for a dedicated dc-dc isolated power converter. The flexibility of this topology allows the adoption of different balancing strategies, which can be used to improve balancing efficiency. The proposed topology was first analyzed through computer simulations, and a laboratory BMS prototype was developed. The results from the simulation and experimental tests validate the topology operation and its performance in transferring energy between the cells and the auxiliary battery. Full article

(This article belongs to the Special Issue Battery Management in Electric Vehicles: Current Status and Future Trends: 2nd Edition)

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15 pages, 13103 KiB

Open AccessArticle

State-of-Health Estimation for Lithium-Ion Batteries Based on Lightweight DimConv-GFNet

by Kehao Huang, Jianqiang Kang, Jing V. Wang, Qian Wang and Oukai Wu

Batteries 2025, 11(5), 174; https://doi.org/10.3390/batteries11050174 - 26 Apr 2025

Viewed by 217

Abstract

The accurate estimation of the state of health (SOH) is crucial for effective battery management systems. This paper proposes a deep learning model dimension-wise convolutions-globalfilter networks (DimConv-GFNet) for lithium-ion battery SOH estimation. Particularly, the DimConv-GFNet comprises the dimension-wise convolutions (DimConv), which collect the [...] Read more.

The accurate estimation of the state of health (SOH) is crucial for effective battery management systems. This paper proposes a deep learning model dimension-wise convolutions-globalfilter networks (DimConv-GFNet) for lithium-ion battery SOH estimation. Particularly, the DimConv-GFNet comprises the dimension-wise convolutions (DimConv), which collect the multi-scale local features from different sensor signals, and lightweight global filter networks (GFNet) to capture long-range dependencies in the Fourier frequency domain. Unlike Transformer attention architectures, GFNet utilizes spectral properties to facilitate global information exchange with a lower computational complexity. Experiments on two datasets with a total of 167 commercial LFP/graphite cells validate the effectiveness of DimConv-GFNet. Although the model shows slightly lower accuracy compared to the DimConv-Transformer baseline, it delivers competitive performance with a root mean squared error (RMSE) of 0.335%, mean absolute error (MAE) of 0.233% and a mean absolute percentage error (MAPE) of 0.230%. Remarkably, the DimConv-GFNet substantially reduces computational demands, requiring fewer than one-third of the Floating Point Operations (FLOPs) and parameters of DimConv-Transformer. These results demonstrate DimConv-GFNet strikes a good balance between accuracy and efficiency, positioning it as a promising solution for efficient and accurate SOH estimation in battery management applications. Full article

(This article belongs to the Special Issue Artificial Intelligence-Based State-of-Health Estimation of Lithium-Ion Batteries—2nd Edition)

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14 pages, 5921 KiB

Open AccessArticle

Study on Mechanical Properties and Microstructural Evolution of Composite Copper Foils Following Long-Term Storage

by Yujie Yan, Haibo Chen, Hang Li, Jing Hu, Ziye Xue, Jianli Zhang, Qiang Chen, Guangya Hou and Yiping Tang

Batteries 2025, 11(5), 173; https://doi.org/10.3390/batteries11050173 - 25 Apr 2025

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Abstract

Composite copper foil, a novel negative electrode current collector developed in recent years, can significantly enhance battery safety and energy density while also conserving metallic resources. It is found that after 9 months of long-term storage, the tensile strength of the composite copper [...] Read more.

Composite copper foil, a novel negative electrode current collector developed in recent years, can significantly enhance battery safety and energy density while also conserving metallic resources. It is found that after 9 months of long-term storage, the tensile strength of the composite copper foil decreases by 9.76%, and the elongation rate drops by 26.32%. The internal texture of the composite copper foil shifts from a highly oriented (111) plane to a more random crystal plane orientation and the bonding strength is significantly improved. The study reveals that the residual stress within the copper layer provides the driving force for the changes in the microstructure; the intermediate PET layer plays a buffering and absorbing role in the stress-release process. It regulates the redistribution of stress, promoting the alteration of the copper layer’s texture and the refinement of grains. Full article

(This article belongs to the Special Issue High-Performance Secondary Batteries: Recent Processes and Future Challenges)

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27 pages, 7505 KiB

Open AccessArticle

Modular Multifunctional Composite Structure for CubeSat Applications: Embedded Battery Prototype Thermal Analysis

by Giorgio Capovilla, Enrico Cestino, Leonardo Reyneri and Federico Valpiani

Batteries 2025, 11(5), 172; https://doi.org/10.3390/batteries11050172 - 23 Apr 2025

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Abstract

The present work aims to develop the current CubeSats architecture. Starting from the framework of project ARAMIS (an Italian acronym for a highly modular architecture for satellite infrastructures), a new concept of smart tiles has been developed, employing multifunctional structures and lightweight, composite [...] Read more.

The present work aims to develop the current CubeSats architecture. Starting from the framework of project ARAMIS (an Italian acronym for a highly modular architecture for satellite infrastructures), a new concept of smart tiles has been developed, employing multifunctional structures and lightweight, composite materials. This enables increased CubeSat mass efficiency and payload volume. An embedded battery tile has been designed, built, and tested from a vibration point of view. In the present work, the LiPo batteries selected for the prototype have been tested with the HPPC testing procedure, to extract their equivalent Randles circuit parameters. Thus, the thermal power dissipation from the batteries can be estimated. With these data, Thermal Desktop simulations of a representative ARAMIS CubeSat are performed, considering LEO orbit and hot/cold cases. Firstly, a parametric analysis was conducted to evaluate the thermal behaviors of various design alternatives. A suitable configuration for the CubeSat was then found, enabling the validation of the embedded battery tile from a thermal point of view. The final configuration includes heaters for the LiPo batteries, a commercial CubeSat skeleton made in aluminum alloy, and a top coating for smart tiles with proper solar absorptivity. Full article

(This article belongs to the Special Issue Rechargeable Batteries)

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23 pages, 10702 KiB

Open AccessReview

Recent Progress in Cathode-Free Zinc Electrolytic MnO₂ Batteries: Electrolytes and Electrodes

by Shiwei Liu, Zhongqi Liang, Hang Zhou, Weizheng Cai, Jiazhen Wu, Qianhui Zhang, Guoshen Yang, Walid A. Daoud, Zanxiang Nie, Pritesh Hiralal, Shiqiang Luo and Gehan A. J. Amaratunga

Batteries 2025, 11(5), 171; https://doi.org/10.3390/batteries11050171 - 23 Apr 2025

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Abstract

Zinc–manganese dioxide (Zn–MnO₂) batteries, pivotal in primary energy storage, face challenges in rechargeability due to cathode dissolution and anode corrosion. This review summarizes cathode-free designs using pH-optimized electrolytes and modified electrodes/current collectors. For electrolytes, while acidic systems with additives (PVP, HAc) [...] Read more.

Zinc–manganese dioxide (Zn–MnO₂) batteries, pivotal in primary energy storage, face challenges in rechargeability due to cathode dissolution and anode corrosion. This review summarizes cathode-free designs using pH-optimized electrolytes and modified electrodes/current collectors. For electrolytes, while acidic systems with additives (PVP, HAc) enhance ion transport, dual-electrolyte configurations (ion-selective membranes/hydrogels) reduce Zn corrosion. Near-neutral strategies utilize nanomicelles/complexing agents to regulate MnO₂ deposition. Moreover, mediators (I⁻, Br⁻, Cr³⁺) reactivate MnO₂ but require shuttle-effect control. For the electrodes/current collectors, electrode innovations including SEI/CEI layers and surfactant-driven phase tuning are introduced. Electrode-free designs and integrated “supercapattery” systems combining supercapacitors with Zn–MnO₂/I₂ chemistries are also discussed. This review highlights electrolyte–electrode synergy and hybrid device potential, paving the way for sustainable, high-performance Zn–MnO₂ systems. Full article

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9 pages, 1696 KiB

Open AccessArticle

Interactions Between Trivalent Elements Enable Ultrastable LDH Cathode for High-Performance Zinc Battery

by Junhua Zeng, Jinlei Gao, Wenyao Lu, Jiashuo Feng and Ting Deng

Batteries 2025, 11(5), 170; https://doi.org/10.3390/batteries11050170 - 23 Apr 2025

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Abstract

Layered double hydroxides (LDHs) are one class of two-dimensional materials, with tunable chemical composition and large interlayer spacing, that is a potential cathode material candidate for aqueous zinc-ion batteries (AZIBs). Nevertheless, the low conductivity and fragile structure of LDH have impeded their practical [...] Read more.

Layered double hydroxides (LDHs) are one class of two-dimensional materials, with tunable chemical composition and large interlayer spacing, that is a potential cathode material candidate for aqueous zinc-ion batteries (AZIBs). Nevertheless, the low conductivity and fragile structure of LDH have impeded their practical application in AZIBs. Herein, a ternary CoMnAl LDH is synthesized via the facile coprecipitation method as the cathode material for AZIB. The interaction between trivalent Al³⁺ and Mn³⁺ not only lowers the redox energy barrier but also enhances the electronic structure, as proved by EIS analysis and DFT simulation. As a result, the synthesized CoMnAl LDH displays a high specific capacity of 238.9 mAh g⁻¹ at 0.5 A g⁻¹, an outstanding rate performance (138.8 mAh g⁻¹ at 5 A g⁻¹), and a stable cyclability (92% capacity retention after 2000 cycles). Full article

(This article belongs to the Special Issue The Breakthrough of Traditional Electrochemical Energy Storage Systems)

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22 pages, 3518 KiB

Open AccessArticle

Microgrid Energy Management Considering Energy Storage Degradation Cost

by Yiming Zhao, Hongrui Li, Changsheng Wan, Dong Du and Bo Chen

Batteries 2025, 11(5), 169; https://doi.org/10.3390/batteries11050169 - 23 Apr 2025

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Abstract

There are many challenges in incorporating the attenuation cost of energy storage into the optimization of microgrid operations due to the randomness of renewable energy supply, the high cost of controlled power generation, and the complexity associated with calculating the cost of battery [...] Read more.

There are many challenges in incorporating the attenuation cost of energy storage into the optimization of microgrid operations due to the randomness of renewable energy supply, the high cost of controlled power generation, and the complexity associated with calculating the cost of battery attenuation. Therefore, this paper proposes a microgrid energy management scheme considering the attenuation cost of energy storage. This scheme analyzes the power generation mode and uncertainty factors of distributed generators in detail. The influence of charge and discharge depth on the cycle life and residual value of the energy storage system was analyzed, and the energy storage attenuation cost model was established. Finally, considering the cost of power generation, environmental treatment, and the deterioration cost of energy storage systems, the objective function of the comprehensive operation cost of microgrids is formulated. The improved sine cosine algorithm (SCA) is used to simulate the energy output optimization of various distributed generators in the microgrid. The results show that the algorithm can effectively reduce the comprehensive operation cost of microgrids and improve their energy utilization efficiency, which proves the practical significance and reference value of the method for microgrid energy management. Full article

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17 pages, 5165 KiB

Open AccessArticle

A Modular Cell Balancing Circuit and Strategy Based on Bidirectional Flyback Converter

by Yipei Wang, Jun-Hyeong Kwon, Seong-Cheol Choi, Guangxu Zhou and Sung-Jun Park

Batteries 2025, 11(5), 168; https://doi.org/10.3390/batteries11050168 - 23 Apr 2025

Viewed by 296

Abstract

In this paper, a modular cell balancing circuit based on a bidirectional flyback converter (BFC) is designed, which is equipped with a symmetrical BFC for each cell. The primary side of all BFCs is in parallel with the battery pack, and the secondary [...] Read more.

In this paper, a modular cell balancing circuit based on a bidirectional flyback converter (BFC) is designed, which is equipped with a symmetrical BFC for each cell. The primary side of all BFCs is in parallel with the battery pack, and the secondary side is connected to the individual cells. Such an input-parallel output-series structure allows for bidirectional and controllable energy transfer among the cells. The control of the charging/discharging for a specific cell can be realized by adjusting the PWM signal on the primary or secondary side of the corresponding BFC. Based on this, three cell balancing strategies are proposed: maximum voltage discharge (MXVD), minimum voltage charge (MNVC), and maximum and minimum voltage balancing (MX&MNB). For MX&MNB, which is essentially a combination of MXVD and MNVC, it controls the maximum voltage cell discharging and minimum voltage cell charging simultaneously, where the energy is transferred directly between the two cells with the largest voltage difference. A cell balancing prototype is built and tested to verify the feasibility and stability of the proposed strategy. All three proposed methods can implement cell balancing simply and effectively, while the MX&MNB provides a faster speed. Full article

(This article belongs to the Special Issue Advanced Control and Optimization of Battery Energy Storage Systems—2nd Edition)

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22 pages, 9495 KiB

Open AccessArticle

SOH Estimation Method for Lithium-Ion Batteries Using Partial Discharge Curves Based on CGKAN

by Shengfeng He, Wenhu Qin, Zhonghua Yun, Chao Wu and Chongbin Sun

Batteries 2025, 11(5), 167; https://doi.org/10.3390/batteries11050167 - 23 Apr 2025

Viewed by 269

Abstract

Accurate estimation of the state of health (SOH) of lithium-ion batteries is essential to ensure the safe and stable operation of equipment such as electric vehicles. To address the limitations in the accuracy and robustness of existing methods under complex operating conditions, a [...] Read more.

Accurate estimation of the state of health (SOH) of lithium-ion batteries is essential to ensure the safe and stable operation of equipment such as electric vehicles. To address the limitations in the accuracy and robustness of existing methods under complex operating conditions, a CNN-BiGRU-KAN (CGKAN) method for SOH estimation based on partial discharge curves is proposed. Firstly, random forest analysis is applied to extract features highly correlated with battery health from the partial discharge curve data. Next, a SOH estimation framework based on the CGKAN model is developed, where 1-Dimensional-Convolutional Neural Networks (1D-CNN) are used to extract deep features from the original data, Bidirectional Gated Recurrent Unit (BiGRU) captures the bidirectional dependencies of the time series, and Kolmogorov–Arnold Networks (KAN) enhances the modeling of complex nonlinear features through its nonlinear mapping capabilities, thereby improving the accuracy of SOH estimation. Finally, multiple experiments under different conditions are conducted, and the results demonstrate that the proposed CGKAN method, by integrating the individual advantages of 1D-CNN, BiGRU, and KAN, efficiently captures complex nonlinear patterns in battery health features and maintains stable performance across various operating conditions. Full article

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Batteries, Volume 11, Issue 5 (May 2025) – 24 articles

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