Batteries

10 pages, 1121 KB

Open AccessArticle

Research on the Active Safety Warning Technology of LIBs Thermal Runaway Based on FBG Sensing

by Yanli Miao, Xiao Tan, Chenying Li, Jianjun Liu, Ling Sa, Xiaohan Li, Zongjia Qiu and Zhichao Ding

Batteries 2026, 12(3), 110; https://doi.org/10.3390/batteries12030110 - 23 Mar 2026

Viewed by 572

Abstract

Lithium-ion batteries (LIBs) may experience thermal runaway (TR) under thermal abuse conditions, posing significant safety risks to energy storage systems, electric vehicles, and portable electronics. To ensure the safety of LIB-powered applications, developing an effective TR early warning method is crucial. This study [...] Read more.

Lithium-ion batteries (LIBs) may experience thermal runaway (TR) under thermal abuse conditions, posing significant safety risks to energy storage systems, electric vehicles, and portable electronics. To ensure the safety of LIB-powered applications, developing an effective TR early warning method is crucial. This study employs polyimide-coated femtosecond fiber Bragg grating (FBG) sensors to investigate TR characteristics in 18,650 LIBs (LiNi_1/3Mn_1/3Co_1/3O₂/graphite), including TR onset temperature determination and the evolution of temperature and radial strain at different states of charge (SOCs). Compared with existing studies, the polyimide-coated femtosecond FBGs employed here offer superior breakage resistance and high-temperature tolerance, enabling more precise temperature and strain measurements. For radial strain monitoring obtained during high-temperature-induced LIBs thermal runaway experiments, temperature compensation was achieved using polyimide-coated femtosecond FBG temperature sensors, yielding higher-accuracy strain evolution profiles. Experimental results demonstrate that the higher-SOC LIBs exhibit more severe TR eruptions, with 1.76× higher peak temperatures and 1.3× greater mass loss than low-SOC LIBs. The proposed scheme pioneers an new approach to effective active safety warning of LIBs thermal runaway. Full article

(This article belongs to the Special Issue Advanced Intelligent Management Technologies of New Energy Batteries)

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20 pages, 5112 KB

Open AccessReview

Recent Advances in Aqueous Zinc Ion Batteries: Energy Storage Mechanisms, Challenges, and Optimization Strategies

by Dong Zhao, Changwei Liu, Tao Chen and Man Li

Batteries 2026, 12(3), 109; https://doi.org/10.3390/batteries12030109 - 23 Mar 2026

Cited by 1 | Viewed by 2548

Abstract

Aqueous zinc-ion batteries (AZIBs) are promising for large-scale grid storage due to inherent safety, low cost, environmental compatibility, high theoretical capacity (820 mAhg⁻¹), and suitable redox potential (−0.763 V vs. SHE). However, practical deployment is hindered by coupled challenges at the [...] Read more.

Aqueous zinc-ion batteries (AZIBs) are promising for large-scale grid storage due to inherent safety, low cost, environmental compatibility, high theoretical capacity (820 mAhg⁻¹), and suitable redox potential (−0.763 V vs. SHE). However, practical deployment is hindered by coupled challenges at the zinc anode–hydrogen evolution, dendrite growth, and corrosion/passivation, which severely limit cycle life and coulombic efficiency. This review systematically summarizes key advances in AZIB research. It first elucidates working principles and four cathode energy storage mechanisms: Zn²⁺ insertion/extraction, H⁺/Zn²⁺ co-insertion, chemical conversion, and dissolution/deposition. Second, it examines four mainstream cathodes (manganese-based, vanadium-based, Prussian blue analogs, and organic compounds), analyzing performance bottlenecks and corresponding optimization via structural modification. Third, it explores functional mechanisms of advanced separators (polymer, inorganic/ceramic composite, MOF-based, and cellulose-based) in regulating uniform Zn²⁺ deposition and suppressing dendrites. Fourth, it summarizes anode optimization strategies: artificial protective layers for interface stabilization, electrolyte additives to modulate Zn²⁺ solvation/deposition, and 3D porous structures to reduce local current density and provide nucleation sites. Finally, key scientific challenges and future directions are discussed—multi-strategy synergy, in situ characterization, practical battery construction, and sustainable technological development, offering theoretical guidance for advancing AZIBs toward large-scale applications. This review aims to provide a comprehensive perspective spanning from materials to systems, and from mechanisms to applications. Its core objective is not merely to list the types of cathode materials, but to establish a logical bridge directly connecting “key challenges” to “optimization strategies,” with a particular emphasis on the issues and solutions related to the cathode side. Full article

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

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26 pages, 5183 KB

Open AccessArticle

Comparative Analysis and PSO-Based Optimization of Battery Technologies for Autonomous Mobile Robots

by Masood Shahbazi, Ebrahim Seidi and Artur Ferreira

Batteries 2026, 12(3), 108; https://doi.org/10.3390/batteries12030108 - 22 Mar 2026

Viewed by 664

Abstract

Autonomous mobile robots are transforming industries from e-commerce logistics to field exploration, but their effectiveness depends on onboard energy storage. This study addresses the challenge of selecting optimal battery technologies for autonomous mobile robots, balancing performance, energy efficiency, thermal stability, and cost across [...] Read more.

Autonomous mobile robots are transforming industries from e-commerce logistics to field exploration, but their effectiveness depends on onboard energy storage. This study addresses the challenge of selecting optimal battery technologies for autonomous mobile robots, balancing performance, energy efficiency, thermal stability, and cost across diverse applications. We focus on lithium-ion, lithium-polymer, and nickel-metal hydride batteries, the most common power solutions, each with distinct advantages and disadvantages in energy density, form factor, thermal stability, and cost. A dynamic modeling and simulation framework in MapleSim evaluated these chemistries under defined and representative operating conditions, tracking state of charge and temperature during charging and discharging. A Particle Swarm Optimization algorithm evaluated 37 battery configurations by thermal stability, energy efficiency, and cost across five use cases. Key results indicate that for logistics and warehousing, lithium nickel manganese cobalt oxide with graphite is optimal; for healthcare, lithium nickel manganese cobalt oxide with lithium titanate oxide excels; for manufacturing, lithium nickel cobalt aluminum oxide with graphite leads; for agricultural robots, lithium manganese oxide with graphite is best; and for exploration and mining, lithium iron phosphate with graphite is most reliable. These results provide a structured basis for battery selection, showing how simulation-driven, multi-criteria decision-making enhances energy management and operational reliability. Full article

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

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37 pages, 7685 KB

Open AccessReview

Comparative Review of Cooling Systems for Lithium-Ion Battery Modules with 21700 Cylindrical Cells

by Leone Martellucci, Roberto Capata and Matteo De Marco

Batteries 2026, 12(3), 107; https://doi.org/10.3390/batteries12030107 - 21 Mar 2026

Cited by 1 | Viewed by 1728

Abstract

The automotive sector is currently undergoing a rapid and complex transition from classic internal combustion engines to hybrid or fully electric propulsion systems, at the core of which is the battery pack. Currently, the battery packs of almost all electric vehicles on the [...] Read more.

The automotive sector is currently undergoing a rapid and complex transition from classic internal combustion engines to hybrid or fully electric propulsion systems, at the core of which is the battery pack. Currently, the battery packs of almost all electric vehicles on the road consist of lithium-ion cells. The thermal management of these cells represents a complex and fundamental challenge, essential not only to ensure optimal vehicle performance but also to guarantee passenger safety. Therefore, this paper examines and compares four main systems used for battery thermal management, highlighting their strengths, weaknesses, and overall effectiveness. First, a standard module comprising 21700 cylindrical cells, representative of automotive applications, is designed. Subsequently, computational fluid dynamics (CFD) thermal analyses of this module are performed to evaluate four different cooling methods: forced air cooling, bottom cold plate cooling, liquid tube cooling, and immersion cooling combined with tab cooling. Finally, an experimental validation is conducted by testing these systems on a physical module, which is subjected to the same electrical discharge profile simulated in the CFD analyses, to verify the effectiveness of the four considered methods. Full article

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

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29 pages, 3082 KB

Open AccessArticle

Multi-Objective Optimization of Thermal and Mechanical Performance of Prismatic Aluminum Shell Lithium Battery Module with Integrated Biomimetic Liquid Cooling Plate

by Yi Zheng and Xu Zhang

Batteries 2026, 12(3), 106; https://doi.org/10.3390/batteries12030106 - 19 Mar 2026

Viewed by 1019

Abstract

Addressing the thermal management challenges of prismatic aluminum shell lithium battery modules in electric vehicles under high-rate charge–discharge conditions, this study proposes a multi-objective optimization design method for integrated biomimetic liquid cooling plates. By integrating various highly efficient heat transfer structures from nature, [...] Read more.

Addressing the thermal management challenges of prismatic aluminum shell lithium battery modules in electric vehicles under high-rate charge–discharge conditions, this study proposes a multi-objective optimization design method for integrated biomimetic liquid cooling plates. By integrating various highly efficient heat transfer structures from nature, including fractal-tree-like networks, leaf vein branching systems, and spider web radial distribution, a novel biomimetic liquid cooling plate topology was constructed. A multi-physics coupled numerical model considering electrochemical heat generation, thermal conduction, convective heat transfer, and thermal stress deformation was established. The NSGA-II algorithm was employed to globally optimize 12 design variables including channel geometric parameters, operating conditions, and structural dimensions, achieving collaborative optimization objectives of maximum temperature minimization, temperature uniformity maximization, pressure drop minimization, and structural lightweighting. The weight coefficients for the four optimization objectives were determined through the Analytic Hierarchy Process (AHP) with verified consistency (CR = 0.02 < 0.10), ensuring rational priority allocation aligned with automotive safety standards. The optimization results demonstrated that compared to the initial design, the optimal solution reduced the maximum temperature under 3C discharge conditions by 9.9% to 34.7 °C, decreased the temperature difference by 31.3% to 3.3 °C, lowered the pressure drop by 24.6% to 2150 Pa, reduced structural mass by 4.0%, and decreased maximum stress by 16.7%. Quantitative comparison with single biomimetic structures under identical boundary conditions showed that the integrated design achieved a 3.3% lower maximum temperature and 25.7% better flow uniformity than the best-performing single structure, demonstrating the synergistic advantages of multi-biomimetic integration. These synergistic performance improvements can be attributed to the hierarchical multi-scale architecture where fractal networks provide macro-scale flow distribution, leaf vein branches ensure meso-scale coverage, and spider web radials achieve micro-scale thermal matching. Long-term cycling tests conducted at 1C/1C rate with 25 ± 1 °C ambient temperature showed that the optimized design maintained a capacity retention rate of 92.3% after 1000 charge–discharge cycles, demonstrating excellent durability. The complex biomimetic channel structure can be fabricated using selective laser melting technology with minimum feature sizes below 0.3 mm, indicating promising manufacturing feasibility. The research findings provide theoretical guidance and technical support for the engineering design of high-performance battery thermal management systems. Full article

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

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23 pages, 14312 KB

Open AccessArticle

Gradient Flow Field Designing to Enhance Mass and Heat Transfer for Air-Cooled Proton Exchange Membrane Fuel Cell Using the Modeling Frame

by Xuemei Li, Beibei Chen, Fei Wang, Zhijun Deng, Yajun Wang and Chen Zhao

Batteries 2026, 12(3), 105; https://doi.org/10.3390/batteries12030105 - 19 Mar 2026

Viewed by 606

Abstract

Structural optimization of the cathode flow field is a viable approach to homogenize multi-physical field distributions and boost the output of air-cooled proton exchange membrane fuel cells (PEMFCs). This work develops a three-dimensional non-isothermal model to systematically evaluate the performance of graded flow [...] Read more.

Structural optimization of the cathode flow field is a viable approach to homogenize multi-physical field distributions and boost the output of air-cooled proton exchange membrane fuel cells (PEMFCs). This work develops a three-dimensional non-isothermal model to systematically evaluate the performance of graded flow channel designs. The results indicate that the graded structure promotes fluid transport in the central zone, thereby improving oxygen distribution uniformity at the gas diffusion layer/catalyst layer (GDL/CL) interface. Compared to the traditional parallel flow channel (with an average oxygen mass fraction of 0.051% and a uniformity index of 0.779), this configuration yields a 6.4% increase in the average oxygen mass fraction and a 0.96% enhancement in distribution uniformity. However, increased gradient flow reduces the flow velocity within the channels and raises the operating temperature, posing challenges for water and thermal management. The curved channel design, featuring longer channels at the ends and shorter channels in the center, compensates for the uneven air supply caused by the fan, thus balancing the flow distribution. Among the tested configurations, the 10° curved structure exhibits optimal performance, achieving the best compromise between gas distribution and liquid water removal. It effectively promotes oxygen diffusion and uniform water distribution, significantly alleviating mass transfer polarization and yielding a more uniform interface temperature distribution due to evaporative cooling. Both excessively small and large curvature angles lead to performance degradation, primarily due to inadequate water removal and flow separation, accompanied by excessive pressure drop, respectively. In contrast, the 10° curved channel strikes an optimal balance, offering significant advantages in overall cell performance and water–thermal management, which provides critical guidance for optimizing PEMFC flow field designs. Full article

(This article belongs to the Special Issue Fuel Cell for Portal and Stationary Applications)

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35 pages, 1537 KB

Open AccessReview

A Comprehensive Analysis of Lithium–Sulfur Batteries: Properties, Challenges, and Applications

by Joshua Meeks, Milo Lawley, Nathan Ly, Renae Maxson, Nolan Mayberry, Subin Antony Jose and Pradeep L. Menezes

Batteries 2026, 12(3), 104; https://doi.org/10.3390/batteries12030104 - 18 Mar 2026

Viewed by 2455

Abstract

Lithium–sulfur (Li–S) batteries have emerged as a promising next-generation energy storage solution as the capacity demands on lithium-ion systems begin to exceed practical limits. In a global push for renewable energy and sustainable practices, Li–S technology offers several compelling advantages. Both lithium and [...] Read more.

Lithium–sulfur (Li–S) batteries have emerged as a promising next-generation energy storage solution as the capacity demands on lithium-ion systems begin to exceed practical limits. In a global push for renewable energy and sustainable practices, Li–S technology offers several compelling advantages. Both lithium and sulfur are relatively inexpensive (especially compared to the transition metals used in lithium-ion cells), and Li–S batteries are easier and less costly to recycle. Moreover, Li–S chemistry carries a theoretical energy density about five times greater than that of current lithium-ion batteries, making it attractive for high-energy-density applications. Because of these advantages, research interest in Li–S batteries remains high despite significant challenges that still limit their performance and lifespan. However, despite these advantages, several fundamental challenges limit the practical deployment of Li–S batteries, including the polysulfide shuttle effect, large volume expansion of sulfur during cycling, low intrinsic electrical conductivity of sulfur and its discharge products, and instability of the lithium metal anode caused by dendrite formation. This paper explains the working principles of Li–S batteries, analyzes the key challenges and recent achievements in their development, and surveys various mechanical engineering applications for which Li–S batteries are being explored, as well as prospects for their future commercialization and sustainability. Full article

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31 pages, 7070 KB

Open AccessArticle

Cross-Condition Lithium-Ion Battery Capacity Multi-Variable Estimation Model Based on Incremental Capacity Curve Features

by Dongxu Han, Yuchang Xing and Nan Zhou

Batteries 2026, 12(3), 103; https://doi.org/10.3390/batteries12030103 - 18 Mar 2026

Viewed by 516

Abstract

Accurate estimation of lithium-ion battery state of health and capacity is critical for intelligent battery management. This study develops a multi-variable cross-condition capacity estimation model based on incremental capacity (IC) curve features. First, the IC curve area is extracted to construct a health [...] Read more.

Accurate estimation of lithium-ion battery state of health and capacity is critical for intelligent battery management. This study develops a multi-variable cross-condition capacity estimation model based on incremental capacity (IC) curve features. First, the IC curve area is extracted to construct a health indicator. To capture the coupled, non-linear effects of temperature and discharge current on capacity fade, a temperature-zoned modeling framework is implemented. Specifically, first-order linear polynomials are applied for room temperature conditions to prevent overfitting, while second-order polynomials with interaction terms are utilized for high and low temperature conditions to model complex degradation behaviors. Furthermore, to mitigate estimation errors caused by individual battery inconsistency and varying initial states across different operating conditions, the capacity retention rate (CRR) and health indicator retention rate metrics are defined and integrated into the estimation framework. Validation across multiple dynamic operating conditions demonstrates that the optimized CRR-based model achieves an average root mean square error of 0.0261 Ah and a mean absolute percentage error of 2.83%. The proposed temperature-zoned approach provides a robust, data-driven methodology for cross-condition battery health monitoring. Full article

(This article belongs to the Special Issue Intelligent Management and Sustainable Development of Lithium-Ion Batteries in Automotive Applications)

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17 pages, 2240 KB

Open AccessArticle

A Grid-Forming Battery Energy System with Mode-Adaptive Virtual Inductance Control

by Lijun Zheng and Xinghu Liu

Batteries 2026, 12(3), 102; https://doi.org/10.3390/batteries12030102 - 16 Mar 2026

Viewed by 579

Abstract

Battery Emergency Mobile Power Systems (BEMPSs) play a critical role in disaster recovery, remote electrification, and grid reinforcement, where resilient, rapidly deployable power supply is essential. However, conventional grid-forming (GFM) control strategies often rely on static parameters, limiting their adaptability during grid disturbances, [...] Read more.

Battery Emergency Mobile Power Systems (BEMPSs) play a critical role in disaster recovery, remote electrification, and grid reinforcement, where resilient, rapidly deployable power supply is essential. However, conventional grid-forming (GFM) control strategies often rely on static parameters, limiting their adaptability during grid disturbances, weak grid conditions, and operational mode transitions. This paper proposes a novel energy-aware adaptive control strategy for GFM inverters, tailored for EMPS applications. First, a multi-mode operation framework is developed to enable seamless transitions among grid-forming, grid-following (GFL), and islanded modes, incorporating a dual-loop circulating current decoupling mechanism to suppress transient current and provide damping. Second, a dynamic virtual inductance regulation scheme is introduced, adaptively modulating output impedance based on DC link energy, PCC voltage fluctuation, and grid strength estimation. Third, an energy-aware control law ensures real-time adjustment of inverter dynamics, enhancing damping performance towards the grid disturbance. Extensive time-domain simulations validate the proposed strategy’s effectiveness under mode switching and power disturbance scenarios. Results demonstrate superior dynamic performance, reduced transient overshoot, and improved system robustness compared to conventional methods, making the proposed controller highly suitable for flexible deployment. Full article

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17 pages, 4143 KB

Open AccessArticle

Simultaneous Optimization of Bulk Ion Transport and Interfacial Stability in Gel Polymer Electrolytes via a Multifunctional Triazole Additive

by Jie Zhao, Yubo Cheng, Maoyi Yi, Chunman Zheng and Qingpeng Guo

Batteries 2026, 12(3), 101; https://doi.org/10.3390/batteries12030101 - 16 Mar 2026

Viewed by 563

Abstract

Gel polymer electrolytes (GPEs) typically suffer from sluggish kinetics and interfacial instability at elevated temperatures and high voltages. Herein, 3-(trifluoromethyl)-1H-1,2,4-triazole (TTA) is employed to construct an ultrathin (~25 μm), robust, and homogeneous GPE. TTA acts as a molecular bridge, significantly improving compatibility between [...] Read more.

Gel polymer electrolytes (GPEs) typically suffer from sluggish kinetics and interfacial instability at elevated temperatures and high voltages. Herein, 3-(trifluoromethyl)-1H-1,2,4-triazole (TTA) is employed to construct an ultrathin (~25 μm), robust, and homogeneous GPE. TTA acts as a molecular bridge, significantly improving compatibility between the PVDF-HFP (Poly(vinylidene fluoride-co-hexafluoropropylene)) matrix and LLZTO (Li_6.4La₃Zr_1.4Ta_0.6O₁₂) fillers to create continuous ion-conducting pathways. Consequently, the TTA-GPEs exhibits high ionic conductivity (0.267 mS cm⁻¹ at room temperature), low activation energy (0.181 eV), and an increased lithium-ion transference number (0.425). Advanced surface analysis reveals that TTA preferentially reacts to form a dense, gradient hierarchical interphase (solid electrolyte interphase/cathode electrolyte interphase, SEI/CEI) enriched with inorganic species (LiF, Li₃N, and Li₂S) on the inner side. This architecture suppresses parasitic reactions and lithium dendrite growth. Accordingly, NCM811(LiNi_0.8Co_0.1Mn_0.1O₂)//Li batteries with TTA-GPEs demonstrate stable cycling at 80 °C and 1C, retaining 57.68% capacity after 125 cycles—significantly outperforming benchmarks. This study offers a molecular engineering strategy to simultaneously optimize bulk transport and interfacial stability for high-energy-density solid-state batteries. Full article

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

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16 pages, 3261 KB

Open AccessArticle

Tailoring Micro- and Mesoporosity in Carbon–Sulfur Cathodes for Improved Lithium–Sulfur Battery Performance

by Ameer Nizami, Zhao Yang, Mustafa Nafis Jahangir, Zacharias Leonidakis, Karim Zaghib, Gilles H. Peslherbe and Xia Li

Batteries 2026, 12(3), 100; https://doi.org/10.3390/batteries12030100 - 16 Mar 2026

Viewed by 933

Abstract

Lithium–sulfur (Li-S) batteries hold great promise for next-generation energy storage, offering high theoretical energy density and cost-effectiveness. However, challenges like sulfur’s low conductivity, polysulfide dissolution, and significant volume changes limit their practical application. This study addresses these issues by investigating porosity-engineered carbon hosts, [...] Read more.

Lithium–sulfur (Li-S) batteries hold great promise for next-generation energy storage, offering high theoretical energy density and cost-effectiveness. However, challenges like sulfur’s low conductivity, polysulfide dissolution, and significant volume changes limit their practical application. This study addresses these issues by investigating porosity-engineered carbon hosts, specifically potassium hydroxide (KOH)-activated Black Pearl carbons (BP2000, BP1300, and BP800). Varying KOH-to-carbon ratios allowed precise tailoring of micro- and mesoporous structures, optimizing sulfur loading, electrolyte infiltration, and ion transport. Composites were characterized by TGA, NLDFT, SEM, XRD, and FTIR and electrochemically (cycling, CV, EIS). The KOH-modified BP2000 1:1 cathode, exhibiting the highest mesopore volume increase, demonstrated superior electrochemical performance, including enhanced cycling stability, rate capability, and reduced charge-transfer resistance. These findings emphasize the importance of optimizing pore distribution in carbon hosts for high-performance Li-S batteries and provide valuable insights for advanced energy storage material design. Full article

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

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30 pages, 9167 KB

Open AccessReview

A Review of Thermal Safety and Management of Second-Life Batteries: Cell Screening, Pack Configuration and Health Estimation

by Md Imran Hasan, Gang Lei, Dylan Lu and Pablo Poblete Durruty

Batteries 2026, 12(3), 99; https://doi.org/10.3390/batteries12030099 - 15 Mar 2026

Cited by 1 | Viewed by 1116

Abstract

Electric vehicle (EV) adoption is generating a rapidly increasing stream of retired lithium-ion batteries for second-life deployment. However, thermal safety concerns continue to limit their reuse. This paper reviews second-life battery (SLB) thermal safety and management and organizes existing work through a mechanism-to-deployment [...] Read more.

Electric vehicle (EV) adoption is generating a rapidly increasing stream of retired lithium-ion batteries for second-life deployment. However, thermal safety concerns continue to limit their reuse. This paper reviews second-life battery (SLB) thermal safety and management and organizes existing work through a mechanism-to-deployment framework linking four domains: degradation mechanisms, cell screening, pack configuration, and monitoring. Evidence indicates that thermal risk depends on the degradation pathway rather than capacity fade. In fact, cells with comparable capacity can exhibit substantially different trigger temperatures depending on whether lithium plating or solid-electrolyte interphase (SEI) growth dominates. Therefore, capacity-based screening is insufficient because cells that satisfy capacity thresholds may still remain thermally unstable. The four domains are tightly coupled: the degradation pathway determines screening requirements; screening outcomes constrain pack design; pack topology influences fault escalation; and together these factors determine what monitoring can reliably detect. This review highlights three gaps and outlines future research directions in the field of SLB thermal safety and management: limited aged-cell thermal characterization by degradation pathway, insufficient diagnostic validation under industrial-throughput conditions, and the incomplete translation of screening outputs into design rules. Full article

(This article belongs to the Special Issue Thermal Runaway and Thermal Management: Toward Safe and Reliable Batteries)

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23 pages, 3712 KB

Open AccessArticle

Nitrogen-Enriched Shell Graphite-Core C–Si–N Composite for Reduced Swelling in Si/Graphite Negative Electrodes

by Jeewon Jang, Seongwoo Lee, Sangyup Lee, Paul Maldonado Nogales, Honggeun Lee, Seunga Yang, Minji Kim, Jeonghun Oh and Soon-Ki Jeong

Batteries 2026, 12(3), 98; https://doi.org/10.3390/batteries12030098 - 13 Mar 2026

Viewed by 951

Abstract

This study reports a graphite-core, multiphase gradient C–Si–N composite architecture for Si-containing graphite-based negative electrodes in lithium-ion batteries. The increase in electrode thickness is used as a practical metric of expansion-driven degradation. The composite is prepared by the simultaneous nitridation and carbonization of [...] Read more.

This study reports a graphite-core, multiphase gradient C–Si–N composite architecture for Si-containing graphite-based negative electrodes in lithium-ion batteries. The increase in electrode thickness is used as a practical metric of expansion-driven degradation. The composite is prepared by the simultaneous nitridation and carbonization of a graphite core–Si precursor using polyvinylpyrrolidone (PVP) as the N source. Scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy indicates a quasi-continuous radial trend in the relative N signal toward the outer shell, consistent with preferential N enrichment near the particle exterior. This spatially distributed N arrangement may spatially separate the Si-rich expansion-prone region from the carbon-rich exterior containing nitrides and other N-bearing species, thereby enabling stress partitioning. The shell architecture is designed to disperse expansion-induced stress and stabilize the electrode–electrolyte interface. During electrochemical cycling, the C–Si–N electrode with 10% PVP preserves its core–shell morphology and exhibits the smallest average electrode thickness expansion (~58% after 40 cycles, based on four independent cells). The reduced thickness growth is discussed in relation to a mechanically robust Si–N matrix (Si₃N₄-like/SiN_x-like), potential Li–N interphase species, and N-containing carbon, together with the post-mortem morphology and electrochemical impedance evolution. This study presents reduced swelling as an electrode-level trend versus nominal PVP addition, along with associated nitride-related signatures, thereby highlighting spatially graded stress buffering as an electrode-level design principle. Full article

(This article belongs to the Special Issue Solid Polymer Electrolytes for Lithium Batteries and Beyond)

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23 pages, 3459 KB

Open AccessReview

The European Battery Regulation and Digital Battery Passport: Prospects and Challenges

by Francesca Soavi, Alessandro Gregucci, Alessandro Liverani, Shoayb Mojtahedi, Elisabetta Petri, Federico Mascetti, Francesco Capodarca and Elyes Bel Hadj Jrad

Batteries 2026, 12(3), 97; https://doi.org/10.3390/batteries12030097 - 11 Mar 2026

Viewed by 1444

Abstract

With the rapid and exponential expansion of the lithium-ion battery (LIB) market, a new regulatory framework has been introduced, centered on the implementation of a Battery Passport (BP) to enhance transparency, traceability, and sustainability across the battery value chain. This review aims to [...] Read more.

With the rapid and exponential expansion of the lithium-ion battery (LIB) market, a new regulatory framework has been introduced, centered on the implementation of a Battery Passport (BP) to enhance transparency, traceability, and sustainability across the battery value chain. This review aims to provide the context in which the BP is being implemented by discussing the reliance of LIBs on critical raw materials (CRMs), as well as the related economic and regulatory aspects of the BP system. Furthermore, it examines ongoing BP initiatives and pilot projects and discusses the challenges and opportunities associated with this tool, highlighting its central role in enabling a circular LIB economy in Europe. A critical analysis from a research-oriented perspective is also provided. Full article

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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

Viewed by 571

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

Viewed by 801

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

Viewed by 1220

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

Viewed by 736

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

Cited by 1 | Viewed by 1510

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

Viewed by 810

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

Viewed by 647

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

Cited by 1 | Viewed by 1505

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

Cited by 1 | Viewed by 6927

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

Viewed by 1529

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

Viewed by 1883

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

Viewed by 977

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

Cited by 1 | Viewed by 708

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

Viewed by 686

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

Viewed by 1297

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

Viewed by 925

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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