Batteries

14 pages, 6088 KB

Open AccessArticle

Facile Synthesis of Salt-Assisted Multiroom Carbon/Vanadium Sulfide Microspheres for Fast and Durable Potassium-Ion Storage

by Jaewoo Lee, Hong Geun Oh and Seung-Keun Park

Batteries 2026, 12(3), 96; https://doi.org/10.3390/batteries12030096 - 10 Mar 2026

Abstract

Potassium-ion batteries hold great promise for large-scale energy storage, but their commercialization is hindered by the large ionic radius of potassium, which causes sluggish kinetics and severe volume expansion in anode materials. To address this, we present a scalable spray-drying strategy coupled with [...] Read more.

Potassium-ion batteries hold great promise for large-scale energy storage, but their commercialization is hindered by the large ionic radius of potassium, which causes sluggish kinetics and severe volume expansion in anode materials. To address this, we present a scalable spray-drying strategy coupled with NaCl salt-templating to synthesize hierarchical porous carbon/vanadium sulfide microspheres (p-V₃S₄/C MS). In this structure, V₃S₄ nanoparticles are uniformly encapsulated within a dextrin-derived amorphous carbon matrix, and pores are formed via selective NaCl etching. This unique architecture accommodates volume fluctuations while providing rapid ion diffusion pathways. As a result, the p-V₃S₄/C MS anode exhibits outstanding electrochemical performance, maintaining a reversible capacity of 107 mA h g⁻¹ after 2000 cycles at 2.0 A g⁻¹, and achieves a high pseudocapacitive contribution of 93% at 2.0 mV s⁻¹. Furthermore, a full cell paired with a Prussian blue (PB) cathode demonstrates practical viability and robust reversibility. Our findings demonstrate that this structural engineering effectively mitigates internal resistance and structural degradation, offering a cost-effective route for mass-producing high-performance anodes for next-generation energy storage. Full article

(This article belongs to the Special Issue Advanced Electrode Materials and Electrolytes for Next-Generation Rechargeable Batteries)

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30 pages, 58601 KB

Open AccessArticle

Advancing Measurement Capabilities in Lithium-Ion Batteries: Exploring the Potential of Fiber Optic Sensors for Thermal Monitoring of Battery Cells

by Florian Krause, Felix Schweizer, Alexandra Burger, Franziska Ludewig, Marcus Knips, Katharina Quade, Andreas Würsig and Dirk Uwe Sauer

Batteries 2026, 12(3), 95; https://doi.org/10.3390/batteries12030095 - 10 Mar 2026

Abstract

This work demonstrates the potential of fiber optic sensors for measuring thermal effects in lithium-ion batteries, using a fiber optic measurement method of Optical Frequency Domain Reflectometry (OFDR). The innovative application of fiber sensors allows for spatially resolved temperature measurement, particularly emphasizing the [...] Read more.

This work demonstrates the potential of fiber optic sensors for measuring thermal effects in lithium-ion batteries, using a fiber optic measurement method of Optical Frequency Domain Reflectometry (OFDR). The innovative application of fiber sensors allows for spatially resolved temperature measurement, particularly emphasizing the importance of monitoring not just the exterior but also the internal conditions within battery cells. Utilizing inert glass fibers as sensors, which exhibit minimal sensitivity to electric fields, opens up new pathways for their implementation in a wide range of applications, such as battery monitoring. The sensors used in this work provide real-time information along the entire length of the fiber. It is shown that using the herein presented novel sensors in a temperature range of 0–

80 ° C

reveals a linear, high-sensitivity thermal measurement characteristic with a local resolution of a few centimeters. Furthermore, this study presents preliminary findings on the potential application of fiber optic sensors in lithium-ion battery (LIB) cells, demonstrating that the steps required for battery integration do not impose any restrictive effects on thermal measurements. Full article

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24 pages, 8686 KB

Open AccessArticle

Performance Improvement of a Honeycomb Battery Thermal Management System Based on Fin–Casing Synergistically Enhanced Heat Transfer

by Liang Tong, Xin Gong, Shenglin Su, Linzhi Xu, Min Liu, Lingyu Chen, Qianqian Xin, Tianqi Yang, Hengyun Zhang and Jinsheng Xiao

Batteries 2026, 12(3), 94; https://doi.org/10.3390/batteries12030094 - 9 Mar 2026

Abstract

With the continuous rise in the energy density of power batteries, battery heat generation has become an increasingly severe issue. Particularly under extreme conditions combining high summer temperatures and high discharge rates, battery thermal safety is facing tremendous challenges. To address this problem, [...] Read more.

With the continuous rise in the energy density of power batteries, battery heat generation has become an increasingly severe issue. Particularly under extreme conditions combining high summer temperatures and high discharge rates, battery thermal safety is facing tremendous challenges. To address this problem, this study proposes a honeycomb liquid cooling–PCM hybrid battery thermal management system (BTMS) based on fin–casing synergistic heat transfer enhancement. We analyzed the effects of the longitudinal fins and thermal conductive casing on the thermal characteristics of the system, further investigated the influence patterns of key factors including fin number, battery spacing and contact thermal resistance on the thermal performance of the honeycomb BTMS, and clarified the action mechanisms of each structure and parameter on battery temperature rise and temperature uniformity. The results show that the fin structure enhances longitudinal heat conduction, improves liquid cooling efficiency, and effectively reduces the maximum battery temperature, while the thermal conductive casing significantly improves battery temperature uniformity. The BTMS with fin–casing synergistic heat transfer enhancement can control the maximum battery temperature and temperature difference within 60 °C and 5 °C, respectively, under extreme operating conditions. Full article

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

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18 pages, 3784 KB

Open AccessArticle

Towards Sustainable Energy Storage: Evaluating the Performance of Three Polymer Electrolytes for Zinc-Ion Batteries

by Roya Rajabi, Shichen Sun, Buke Wu, Jamil Khan and Kevin Huang

Batteries 2026, 12(3), 93; https://doi.org/10.3390/batteries12030093 - 9 Mar 2026

Abstract

Polymer electrolytes have been explored as an alternative to conventional aqueous electrolytes in zinc-ion batteries, particularly for flexible and wearable applications. Despite the increasing interest in polymer electrolyte-based zinc-ion batteries (ZIBs), their development is still in its early stages due to various challenges. [...] Read more.

Polymer electrolytes have been explored as an alternative to conventional aqueous electrolytes in zinc-ion batteries, particularly for flexible and wearable applications. Despite the increasing interest in polymer electrolyte-based zinc-ion batteries (ZIBs), their development is still in its early stages due to various challenges. In this study, we investigated three promising polymer electrolytes: CSAM (carboxyl methyl chitosan with acrylamide monomer), PAM (polyacrylamide monomer hydrogel electrolyte), and p-PBI (phosphate-doped polybenzimidazole solid electrolyte) with Zn(ClO₄)₂ and Zn(OTf)₂, as electrolytes for zinc-ion batteries. The p-PBI solid electrolyte showed high mechanical stability and improved resistance to short-circuiting during cycling. The presence of carboxyl groups in CSAM and the existence of O-H bonding facilitated ion movement, resulting in enhanced ionic conductivity and preventing dendrite formation. Incorporating these hydrogels with high-performance zinc salts, such as zinc triflate (Zn(OTf)₂), resulted in stable symmetric cell cycling over 4000 h with a uniform voltage profile under 1 mA/cm² and a low overpotential of around 53 mV cycling with CSAM. Rate-dependent full-cell testing showed that the PBI solid electrolyte delivers higher capacity retention at different current densities, whereas CSAM exhibits markedly better long-term stability, even at low voltages, owing to its effective dendrite suppression, which helps preserve cathode performance over extended cycling. Full article

(This article belongs to the Special Issue Zinc-Ion Batteries: Recent Progress and Prospects)

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32 pages, 5012 KB

Open AccessReview

A Review of Modelling, State of Charge Estimation and Management Methods of EV Lithium-Ion Batteries

by Moayad Albakri and Ahmed Darwish

Batteries 2026, 12(3), 92; https://doi.org/10.3390/batteries12030092 - 8 Mar 2026

Abstract

Electric Vehicles (EVs) can contribute significantly to reducing greenhouse gas emissions and addressing climate change problems. Modern EVs are primarily powered by electrochemical batteries such as lead-acid (Pb-acid), nickel-metal hydride (NiMH), sodium-ion (Na-ion), solid-state and lithium-ion (Li-ion) batteries. When compared to other battery [...] Read more.

Electric Vehicles (EVs) can contribute significantly to reducing greenhouse gas emissions and addressing climate change problems. Modern EVs are primarily powered by electrochemical batteries such as lead-acid (Pb-acid), nickel-metal hydride (NiMH), sodium-ion (Na-ion), solid-state and lithium-ion (Li-ion) batteries. When compared to other battery types, Li-ion batteries are the most suitable for EV applications due to their practical features such as their high energy density, high charging and discharging efficiency and extended lifetime. However, the main risk of Li-ion batteries is that they are exposed to thermal runaway phenomena, which raises severe concerns about the safety of EV propulsion systems. Thermal runaways should be considered carefully as they cannot be stopped once they start and can lead to battery explosion. One of the main reasons leading to this phenomenon is abusing the state of charge (SoC) of the battery. Therefore, the battery management system (BMS) plays a crucial role in mitigating the stimulation of the thermal runaway process by accurately estimating and properly managing the battery cells. To help researchers and designers with understanding this matter, this paper proposes a review of the most effective SoC estimation methods for EV Li-ion batteries and links these methods with practical energy management systems in the EV market. Full article

(This article belongs to the Special Issue Towards a Smarter Battery Management System: 3rd Edition)

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18 pages, 3731 KB

Open AccessArticle

Hydrothermal Synthesis and Electrochemical Properties of SnS₂/N Anode Material for Lithium-Ion Batteries

by Wei Liu, Longhua Zhang, Jingbo Zhang, Ming Li, Yu He, Shipin Wang and Hewei Liu

Batteries 2026, 12(3), 91; https://doi.org/10.3390/batteries12030091 - 6 Mar 2026

Abstract

Although tin disulfide (SnS₂) possesses a theoretical specific capacity (645 mAh g⁻¹) significantly superior to that of commercial graphite, along with the merits of Earth abundance and cost-effectiveness, its commercial application as an anode material for lithium-ion batteries (LIBs) [...] Read more.

Although tin disulfide (SnS₂) possesses a theoretical specific capacity (645 mAh g⁻¹) significantly superior to that of commercial graphite, along with the merits of Earth abundance and cost-effectiveness, its commercial application as an anode material for lithium-ion batteries (LIBs) is severely hindered by substantial volume expansion during cycling. Herein, N-doped SnS₂ composites featuring a stacked hexagonal nanosheet architecture were synthesized via a facile one-step hydrothermal strategy. The incorporation of nitrogen significantly bolsters the long-term cycling stability of the electrode during charge/discharge processes. Electrochemical tests results reveal that the composite delivers an initial specific capacity of 500.8 mAh g⁻¹ at a current density of 0.5 A g⁻¹. Following 10 stabilization cycles, the capacity is recorded at 394.9 mAh g⁻¹, and notably, it increases to 481.66 mAh g⁻¹ after 500 cycles, corresponding to a high capacity retention of 96.17%. This superior performance is attributed to the introduced nitrogen, which provides abundant active sites and facilitates the formation of a robust solid electrolyte interphase (SEI) film. Furthermore, density functional theory (DFT) calculations demonstrate that N-doping narrows the band gap of SnS₂, thereby improving electrical conductivity and electron transport efficiency. Full article

(This article belongs to the Special Issue High Capacity Anode Materials for Lithium-Ion Batteries)

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22 pages, 3339 KB

Open AccessArticle

Particle Velocity Measurement in Battery Thermal Runaway Jets Using an Enhanced Deep Learning and Adaptive Matching Framework

by Xinhua Mao, Zhimin Chen, Mengqi Zhang, Jinwei Sun and Chengshan Xu

Batteries 2026, 12(3), 90; https://doi.org/10.3390/batteries12030090 - 6 Mar 2026

Abstract

High-speed solid particles ejected during battery thermal runaway pose severe safety threats, yet their velocity measurement is hindered by high density, microscopic size, and intense glare. This study proposes a non-intrusive velocimetry framework that integrates an enhanced single-stage object detector with a structural [...] Read more.

High-speed solid particles ejected during battery thermal runaway pose severe safety threats, yet their velocity measurement is hindered by high density, microscopic size, and intense glare. This study proposes a non-intrusive velocimetry framework that integrates an enhanced single-stage object detector with a structural similarity matching algorithm. The detector incorporates specialized feature extraction modules and a high-resolution layer to identify microscopic targets in extreme environments, while the matching algorithm employs adaptive direction constraints to ensure precise trajectory tracking. Experimental validation demonstrates that the framework achieves a mean average precision of 92.7% and supports real-time processing. The method successfully quantifies a three-stage velocity evolution in battery failure events, identifying a peak particle speed exceeding 120 m/s. These findings provide critical kinematic data for optimizing battery safety structures and modeling fire propagation mechanisms. Full article

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24 pages, 1983 KB

Open AccessArticle

An Integrated Hydrometallurgical–Electrodialysis Process for High-Purity Lithium Carbonate Recovery from Battery Waste

by Jose Luis Aldana, Lourdes Yurramendi, Javier Antoñanzas, Javier Nieto and Carmen del Río

Batteries 2026, 12(3), 89; https://doi.org/10.3390/batteries12030089 - 5 Mar 2026

Abstract

The rapid increase in end-of-life lithium-ion batteries demands sustainable recycling routes for lithium recovery. This work presents a novel integrated hydrometallurgical–electrodialysis process designed specifically for recovering lithium from off-specification NMC cathode materials while enabling full reagent recyclability. Selective leaching with oxalic acid was [...] Read more.

The rapid increase in end-of-life lithium-ion batteries demands sustainable recycling routes for lithium recovery. This work presents a novel integrated hydrometallurgical–electrodialysis process designed specifically for recovering lithium from off-specification NMC cathode materials while enabling full reagent recyclability. Selective leaching with oxalic acid was optimised by setting the water-to-oxalic acid dihydrate ratio (H₂O/OA·2H₂O) to 7.3:1 w/w, achieving 81% lithium extraction at room temperature within 2 h while limiting the co-dissolution of Ni, Co and Mn to 0.2%, 1.6% and 1.7% by weight, respectively. The resulting leachate was processed in a four-chamber electrodialysis cell equipped with two Nafion 117 cation-exchange membranes and one Neosepta AMX-fmg anion-exchange membrane operating at −1.6 V versus Ag/AgCl, enabling 96% lithium recovery and 98% oxalic acid recovery. The regenerated oxalic acid stream (41.8 g L⁻¹) was fully restored to its initial concentration and reused in successive cycles without performance loss. Subsequent precipitation of lithium with Na₂CO₃ yielded 99.3%-pure Li₂CO₃. This combined leaching–electrodialysis–precipitation presents a high selectivity, low-waste, circular recovery system, offering a scientifically original approach that integrates reagent regeneration with high-purity lithium production. Full article

(This article belongs to the Special Issue Selected Papers from Circular Materials Conference 2025)

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34 pages, 3542 KB

Open AccessReview

Thermal Runaway in Lithium-Ion Batteries: A Review of Mechanisms, Prediction Approaches, and Mitigation Strategies

by Zeyu Chen, Jiakai Zhang, Chengxin Liu, Chengyan Yang and Shuxian Chen

Batteries 2026, 12(3), 88; https://doi.org/10.3390/batteries12030088 - 3 Mar 2026

Abstract

Thermal runaway is one of the most critical safety challenges limiting the widespread deployment of lithium-ion batteries in electric vehicles, energy storage systems, and aerospace applications. With the continuous increase in battery energy density, the fault-to-failure transition becomes increasingly rapid, which makes early [...] Read more.

Thermal runaway is one of the most critical safety challenges limiting the widespread deployment of lithium-ion batteries in electric vehicles, energy storage systems, and aerospace applications. With the continuous increase in battery energy density, the fault-to-failure transition becomes increasingly rapid, which makes early detection and effective intervention quite difficult. This review systematically summarizes the fundamental mechanisms underlying thermal runaway that drive the escalation of battery hazards. Existing thermal runaway prediction and early warning approaches are comprehensively classified into electrical, thermal, mechanical/gas, and data-driven categories. The detection principles, performance characteristics, and current limitations are critically analyzed. Furthermore, research progress in mitigation and suppression, including system-level thermal management, material-level approach, and structure modification, is discussed. This work aims to support the development of advanced early-warning technologies and to provide guidance for the design of safer next-generation lithium-ion battery systems. Full article

(This article belongs to the Topic Battery Design and Management, 2nd Edition)

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14 pages, 4601 KB

Open AccessArticle

Toward the Commercialization of Lithium Manganese Iron Phosphate for Advanced High-Energy Lithium-Ion Batteries and Beyond

by Atiyeh Nekahi and Karim Zaghib

Batteries 2026, 12(3), 87; https://doi.org/10.3390/batteries12030087 - 3 Mar 2026

Abstract

Lithium manganese iron phosphate [LiMn_xFe_1−xPO₄ (x ≤ 0.5)]-based cathode materials were synthesized via a hydrothermal method to investigate their composition effect on structure and electrochemical performance. The X-ray diffraction results confirmed a single-phase olivine structure (Pnma) for all [...] Read more.

Lithium manganese iron phosphate [LiMn_xFe_1−xPO₄ (x ≤ 0.5)]-based cathode materials were synthesized via a hydrothermal method to investigate their composition effect on structure and electrochemical performance. The X-ray diffraction results confirmed a single-phase olivine structure (Pnma) for all the compositions, with minor lithium phosphate (Li₃PO₄) impurities detected at high manganese (Mn) contents (x ≥ 0.4). The morphological evolution from small particles with low Mn content to compact rod-like particles at x = 0.3 indicates optimized crystal growth and improved interparticle connectivity. Electrochemical testing revealed that the discharge capacity initially increased with the substituted Mn content to a maximum of 140 mAh g⁻¹ at 0.5 C for LiMn_0.3Fe_0.7PO₄/C with remarkable cycling stability. This high capacity is attributed to the activation of Fe²⁺/Fe³⁺ and Mn²⁺/Mn³⁺ redox couples and the minimal formation of electrochemically inactive phases. Further Mn incorporation (x > 0.3) caused structural distortion, Li₃PO₄ formation, and overall capacity loss. Codoping with Mg (LiMg_0.05Mn_xFe_1−xPO₄) improved stability but lowered discharge capacity owing to the electrochemical inactivity of Mg²⁺ and impurity formation. Notably, an optimal x value of ~0.3 exhibited an effective balance between high energy density, rate capability, and structural integrity in Mn-doped LiFePO₄ cathodes for next-generation lithium-ion batteries. Full article

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

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24 pages, 4694 KB

Open AccessArticle

AI-Driven Thermal Management Optimization for Lithium-Ion Battery Packs: A Surrogate Model Approach to Cell Spacing Design

by Florin Mariasiu, Ioan Szabo and George E. Mariasiu

Batteries 2026, 12(3), 86; https://doi.org/10.3390/batteries12030086 - 2 Mar 2026

Abstract

The article presents the possibilities of integrating artificial intelligence (through specific machine learning techniques) in the design and construction process of a battery in order to optimize its thermal management. The workflow starts from CFD thermal simulations (1C-rate) of a battery (16 Li-ion [...] Read more.

The article presents the possibilities of integrating artificial intelligence (through specific machine learning techniques) in the design and construction process of a battery in order to optimize its thermal management. The workflow starts from CFD thermal simulations (1C-rate) of a battery (16 Li-ion cells, type 18650, 4 × 4 arrangement), and based on the results, a complex thermal landscape is created through radial basis function (Rbf) interpolation. Furthermore, a robust neural network (NN) model is proposed and validated through the obtained performances, which is used further for the optimization of the design space (DSO) and multi-objective optimization (MOO) processes. The obtained results show that for DSO, a cell spacing of 1.37 mm is proposed for a maximum cell temperature of 25.53 °C, and in the case of MOO, a cell spacing of 2.64 mm (for minimum fan energy consumption). The main conclusion of the obtained results shows that the use of the NN model as a surrogate (the Digital Twin of a physical model) presents two great advantages in the process of designing a battery: running a CFD simulation for each point on the 2D grid would take hours, while the NN model can generate the entire map and find the optimum in less than 2 s, and moreover, thousands of additional points can be evaluated to find the thin limit of optimal models, effectively filtering out thousands of energy-consuming “suboptimal” configurations. Full article

(This article belongs to the Special Issue Artificial Intelligence-Based State-of-Health Estimation of Lithium-Ion Batteries: 3rd Edition)

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22 pages, 10243 KB

Open AccessArticle

A Novel Empirical Degradation-Guided Transformer–GRU Network for Predicting Battery Capacity Degradation

by Xiandao Lei, Chenyu Liu, Zeping Chen, Jin Fang, Shanshan Guo and Caiping Zhang

Batteries 2026, 12(3), 85; https://doi.org/10.3390/batteries12030085 - 2 Mar 2026

Abstract

Battery ageing is inevitable during operation, leading not only to performance degradation but to potential safety concerns. Consequently, accurate prediction of the state of health (SOH) of lithium-ion batteries is crucial for ensuring their safety and reliability. This study proposed a novel hybrid [...] Read more.

Battery ageing is inevitable during operation, leading not only to performance degradation but to potential safety concerns. Consequently, accurate prediction of the state of health (SOH) of lithium-ion batteries is crucial for ensuring their safety and reliability. This study proposed a novel hybrid neural network architecture that integrates a transformer module, an empirical degradation (ED) model, and a gated recurrent unit (GRU). The transformer module enhances the global representation of the feature sequence, while the ED model comprehensively considers the impact of temperature on the rate of battery capacity degradation, compensating the un-interpretability of the transformer architecture in predicting SOH. In addition, pseudo-incremental capacity curves have been obtained using charging fragments from multi-stage constant current fast charging, which solves the issue of extracting mechanism features under fast charging conditions. Experimental results demonstrate that, across a wide temperature range, the model maintains a low average RMSE between 0.43% and 0.59% for prediction horizons of 4 to 128 cycles. Specifically, the average RMSE is 0.87% at −5 °C and 0.37% between 25 °C and 55 °C. Compared to standalone data-driven models, the proposed hybrid architecture reduces prediction error by approximately 50% at 25 °C, exhibiting superior predictive performance and robustness. Full article

(This article belongs to the Special Issue Battery Management Systems Based on Electrochemical Impedance Spectroscopy)

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26 pages, 12290 KB

Open AccessArticle

State of Charge Estimation Method for Lithium-Ion Batteries Based on Online Parameter Identification and QPSO-AUKF

by Hai Guo, Zhaohui Li, Haoze Xue and Jing Luo

Batteries 2026, 12(3), 84; https://doi.org/10.3390/batteries12030084 - 1 Mar 2026

Abstract

Accurate estimation of the state of charge (SOC) is essential for the safe and efficient operation of lithium-ion batteries. Conventional Adaptive Unscented Kalman Filter (AUKF) methods often exhibit limited accuracy, primarily due to the empirical selection of process and measurement noise covariance matrices. [...] Read more.

Accurate estimation of the state of charge (SOC) is essential for the safe and efficient operation of lithium-ion batteries. Conventional Adaptive Unscented Kalman Filter (AUKF) methods often exhibit limited accuracy, primarily due to the empirical selection of process and measurement noise covariance matrices. To overcome this limitation, this study proposes a QPSO-AUKF algorithm based on a second-order RC equivalent circuit model, which integrates Quantum-behaved Particle Swarm Optimization (QPSO) with online parameter identification. In this approach, the QPSO algorithm optimizes the noise covariance matrices, which are subsequently used within the AUKF framework for SOC estimation. MATLAB R2020a simulations conducted on the Maryland and Wisconsin datasets demonstrate that the QPSO-AUKF reduces the root mean square error (RMSE) by more than 60% compared with the conventional AUKF, indicating a significant improvement in SOC estimation accuracy. Full article

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15 pages, 2034 KB

Open AccessArticle

State of Health Estimation of Lithium-Ion Batteries Based on Voltage Data Segment Hybrid Model

by Zhenhan Zou, Xiangyang Xia, Chaofeng Zhang, Jiahui Yue, Boyan Xia and Caibo Zhou

Batteries 2026, 12(3), 83; https://doi.org/10.3390/batteries12030083 - 28 Feb 2026

Abstract

The health state estimation of lithium-ion batteries are the essential issues for the safety of energy storage stations. The important indicators often focus on the battery capacity and internal resistance. However, the measurement of capacity requires a complete charge/discharge cycle, and the measurement [...] Read more.

The health state estimation of lithium-ion batteries are the essential issues for the safety of energy storage stations. The important indicators often focus on the battery capacity and internal resistance. However, the measurement of capacity requires a complete charge/discharge cycle, and the measurement of internal resistance requires additional equipment. To solve the above problems, based on the voltage segment under the constant-current discharge condition of lithium-ion battery, this paper takes the sharp voltage drop of the initial discharge segment as a new healthy factor. Furthermore, facing the possibility that the new healthy factor data is polluted by noise, this factor data is reconstructed to reduce noise through multi-order Bezier curve. Subsequently, an empirical degradation hybrid model is constructed with the number of cycles. On this basis, the battery healthy state is defined by voltage segment and a new healthy state estimation model is proposed. The feasibility and effectiveness of the proposed degradation model and estimation model are verified by the aging data published by NASA and experimental platform. Full article

(This article belongs to the Special Issue 10th Anniversary of Batteries: Battery Health, Aging and Degradation Mechanisms)

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19 pages, 5093 KB

Open AccessArticle

Improvement of Cycling Stability of Core–Shell Structured Ni-Rich NMC Cathodes by Using a Tungsten Oxide Stabilization Interlayer

by Bilal Tasdemir, Svitlana Krüger, Pinank Sohagiya, Apurba Ray and Bilge Saruhan

Batteries 2026, 12(3), 82; https://doi.org/10.3390/batteries12030082 - 27 Feb 2026

Abstract

The growing demand for higher-energy lithium-ion batteries, encompassing consumer electronics, stationary grid storage, and electric mobility to specialized sectors like aerospace, medical devices, and industrial robotics, requires cathode materials that offer higher capacity while remaining cost-effective. This trend has intensified the development of [...] Read more.

The growing demand for higher-energy lithium-ion batteries, encompassing consumer electronics, stationary grid storage, and electric mobility to specialized sectors like aerospace, medical devices, and industrial robotics, requires cathode materials that offer higher capacity while remaining cost-effective. This trend has intensified the development of nickel-rich LiNi_1−x−yMn_xCo_yO₂ (NMC) systems. However, high-Ni NMCs such as LiNi_0.9Mn_0.05Co_0.05O₂ (NMC90) suffer from limited thermal and cycling stability. Core–shell architectures using LiNi_0.6Mn_0.2Co_0.2O₂ (NMC622) as a shell can partially alleviate these drawbacks, but structural degradation caused by interdiffusion between the core and shell persists as a major challenge. This study investigates whether a tungsten oxide interlayer can act as a protective barrier that suppresses interdiffusion, stabilizes the crystal structure, and improves long-term electrochemical performance. In this work, NMC cathode powders were synthesized via a one-pot oxalate co-precipitation route, followed by structural characterization using X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and ion scattering spectroscopy (ISS). Electrochemical performance, including capacity retention, cycling stability, and internal resistance, was evaluated through galvanostatic charge–discharge (GCD) testing and electrochemical impedance spectroscopy (EIS). The core–shell configuration delivered higher specific discharge capacity compared to the individually synthesized core-only and shell-only reference materials, and the incorporation of a tungsten oxide interlayer resulted in a twofold increase in cycle life. These results demonstrate that tungsten oxide effectively enhances cycling stability by inhibiting core–shell interdiffusion, offering a promising pathway toward more durable high-Ni NMC cathodes. Full article

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

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20 pages, 1673 KB

Open AccessArticle

A Model for State-of-Health, Swelling and Out-of-Plane Stress Evolution in Lithium-Ion Batteries

by Marios Mantelos, Peter Gudmundson and Artem Kulachenko

Batteries 2026, 12(3), 81; https://doi.org/10.3390/batteries12030081 - 26 Feb 2026

Abstract

Module- and pack-level mechanical design of lithium-ion batteries in electric vehicles is a primary driver of swelling-induced stack pressure and spatially varying ageing. Current practice remains largely empirical or data-driven and configuration-specific, limiting the ability to predict how design changes translate into local [...] Read more.

Module- and pack-level mechanical design of lithium-ion batteries in electric vehicles is a primary driver of swelling-induced stack pressure and spatially varying ageing. Current practice remains largely empirical or data-driven and configuration-specific, limiting the ability to predict how design changes translate into local pressure heterogeneity and state-of-health (SOH) loss. This motivates a compact chemo-mechanical model that maps packaging boundary conditions to pressure, swelling, and SOH evolution with few interpretable parameters. This study introduces finite-element-ready constitutive laws that couple reversible and irreversible swelling to SOH and through-thickness pressure, covering three boundary cases reported in literature: constant pressure, thickness clamp after an initial preload, and flexible support. Parameters are identified from different published datasets, and the model is validated against independent constraint scenarios. Good quantitative agreement is shown with averaged RMSE of 1.16% for SOH and 0.16 [MPa] for pressure evolution. Variance-based sensitivity analysis shows SOH uncertainty dominated by the damage-law parameters of the proposed constitutive relationship, whereas pressure evolution is primarily controlled by irreversible swelling and the non-linear through-thickness stiffness, indicating calibration priorities for engineering design studies. The framework is intended for fast comparative analyses of individual cells under a controlled environment. Further extensions, including SOC-dependent mechanics, refined hysteresis, temperature, and C-rate variations require dedicated datasets and are left for future work. Full article

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

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26 pages, 1132 KB

Open AccessArticle

Structure–Property Relationships of Recycled Lithium-Ion Battery Cathodes: Microstructure Optimization Using Virtual Materials Testing

by Lukas Fuchs, Philipp Rieder, Donal P. Finegan, Francois Usseglio-Viretta, Jeffery Allen, Melissa Popeil, Orkun Furat and Volker Schmidt

Batteries 2026, 12(3), 80; https://doi.org/10.3390/batteries12030080 - 26 Feb 2026

Abstract

The increasing demand for sustainable battery technologies requires effective recycling strategies for end-of-life lithium-ion battery cathodes. In this study, virtual materials testing, a well-established framework for modeling conventionally manufactured NMC-based cathodes, is applied to partially recycled cathodes. To this end, virtual cathodes consisting [...] Read more.

The increasing demand for sustainable battery technologies requires effective recycling strategies for end-of-life lithium-ion battery cathodes. In this study, virtual materials testing, a well-established framework for modeling conventionally manufactured NMC-based cathodes, is applied to partially recycled cathodes. To this end, virtual cathodes consisting of mixtures of pristine and recycled NMC particles are utilized to systematically analyze structure–property relationships depending on mixing ratios and different spatial arrangement strategies. For this purpose, a stochastic 3D model is developed that is capable of generating virtual cathodes with arbitrary volume fractions of active materials and mixing ratios of pristine and recycled NMC particles. Particularly, the stochastic 3D model can mimic the different size distributions of pristine and recycled particles that are observed in image data. Additionally, the model allows the structuring of pristine and recycled NMC either uniformly mixed or layer-wise arranged, mimicking single- and dual-layer cathodes. Subsequently, a systematic computational analysis is conducted to assess the influence of increasing active material ratios of recycled particles, ranging from 0 % to 100 %, while maintaining a constant overall active material volume fraction. The impact of particle mixing on cathode performance is evaluated by examining transport-relevant geometrical descriptors and effective properties, such as geodesic tortuosity, specific surface area, and tortuosity factor. 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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35 pages, 12319 KB

Open AccessReview

A Comprehensive Review on the Rapid Development of Silicon/MXene Nanocomposites for Lithium-Ion Battery Applications

by Narasimharao Kitchamsetti, Sungwook Mhin and HyukSu Han

Batteries 2026, 12(3), 79; https://doi.org/10.3390/batteries12030079 - 24 Feb 2026

Abstract

Silicon (Si) has attracted extensive attention as a promising anode material for next-generation lithium-ion batteries (LIBs) due to its ultra-high theoretical capacity, low lithiation potential, and economic advantages. However, drastic volume expansion during cycling and slow reaction kinetics severely compromise its structural stability [...] Read more.

Silicon (Si) has attracted extensive attention as a promising anode material for next-generation lithium-ion batteries (LIBs) due to its ultra-high theoretical capacity, low lithiation potential, and economic advantages. However, drastic volume expansion during cycling and slow reaction kinetics severely compromise its structural stability and practical application. Recently, two-dimensional (2D) MXenes have been explored as effective functional components in Si-based electrodes because of their excellent electrical conductivity, high specific surface area, adjustable surface terminations, and mechanical robustness. When integrated with Si, MXenes serve as conductive matrices that alleviate volumetric stress, enhance charge transport, and accelerate electron/ion diffusion. Consequently, Si/MXene nanocomposites (NCs) exhibit significantly improved lithium (Li) storage performance. This review outlines recent advances in Si/MXene NCs, covering fabrication strategies, structural engineering, and various configurations, including particulate materials, three-dimensional (3D) architectures, films, and fibrous systems, and establishes the relationship between structural design and electrochemical behavior. Remaining challenges and prospective research directions are also discussed to guide the development of high-energy-density LIB anodes. Full article

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30 pages, 3492 KB

Open AccessArticle

Multi-Objective Optimization of CPCM–Liquid Cooling Hybrid Thermal Management Systems for Lithium-Ion Batteries via NSGA-II Optimized Artificial Neural Networks

by Qianqian Xin, Xu Zhang, Tianqi Yang, Hengyun Zhang and Jinsheng Xiao

Batteries 2026, 12(3), 78; https://doi.org/10.3390/batteries12030078 - 24 Feb 2026

Abstract

Considering the synergistic optimization design of battery thermal safety and system economy in extreme environments, a hybrid lithium-ion battery thermal management system (BTMS) employing composite phase change material (CPCM) with liquid cooling is proposed by comparing four BTMSs of pure air cooling, pure [...] Read more.

Considering the synergistic optimization design of battery thermal safety and system economy in extreme environments, a hybrid lithium-ion battery thermal management system (BTMS) employing composite phase change material (CPCM) with liquid cooling is proposed by comparing four BTMSs of pure air cooling, pure CPCM, pure liquid cooling, and the hybrid cooling using CPCM and liquid cooling. The proposed hybrid cooling system demonstrates the capability to maintain the maximum battery temperature at 45.27 °C under extreme operating conditions, including elevated ambient temperatures of 40 °C combined with 5C discharge rate. Notably, this thermal regulation performance is achieved without requiring additional power input, highlighting the energy-efficient design of the system. Further, to address the critical challenge of thermal runaway prevention under summer extreme temperature up to 50 °C, an artificial neural network (ANN) model is established for the hybrid cooling, integrated with the non-dominated sorting genetic algorithm II (NSGA-II) algorithm, leading to the maximum temperature controlled at 48.68 °C and minimum system power consumption of 158 W, achieving a 12.1% reduction in thermal fluctuation amplitude and a 5.9% reduction in power consumption compared to initial design and optimal solutions, respectively. The proposed BTMS introduces the NSGA-II-ANN model for multi-objective collaborative optimization to solve the contradiction between thermal safety and energy consumption under extreme working conditions, enhancing the safety measures of power batteries and economic viability for electric vehicles. Full article

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

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