Batteries

18 pages, 3442 KiB

Open AccessArticle

Multi-Step Temperature Prognosis of Lithium-Ion Batteries for Real Electric Vehicles Based on a Novel Bidirectional Mamba Network and Sequence Adaptive Correlation

by Hongyu Shen, Yuefeng Liu, Qiyan Zhao, Guoyue Xue, Tiange Zhang and Xiuying Tan

Batteries 2024, 10(10), 373; https://doi.org/10.3390/batteries10100373 - 21 Oct 2024

Viewed by 1764

Abstract

The battery systems of electric vehicles (EVs) are directly impacted by battery temperature in terms of thermal runaway and failure. However, uncertainty about thermal runaway, dynamic conditions, and a dearth of high-quality data sets make modeling and predicting nonlinear multiscale electrochemical systems challenging. [...] Read more.

The battery systems of electric vehicles (EVs) are directly impacted by battery temperature in terms of thermal runaway and failure. However, uncertainty about thermal runaway, dynamic conditions, and a dearth of high-quality data sets make modeling and predicting nonlinear multiscale electrochemical systems challenging. In this work, a novel Mamba network architecture called BMPTtery (Bidirectional Mamba Predictive Battery Temperature Representation) is proposed to overcome these challenges. First, a two-step hybrid model of trajectory piecewise–polynomial regression and exponentially weighted moving average is created and used to an operational dataset of EVs in order to handle the problem of noisy and incomplete time-series data. Each time series is then individually labeled to learn the representation and adaptive correlation of the multivariate series to capture battery performance variations in complex dynamic operating environments. Next, a prediction method with multiple steps based on the bidirectional Mamba is suggested. When combined with a failure diagnosis approach, this scheme can accurately detect heat failures due to excessive temperature, rapid temperature rise, and significant temperature differences. The experimental results demonstrate that the technique can accurately detect battery failures on a dataset of real operational EVs and predict the battery temperature one minute ahead of time with an MRE of 0.273%. Full article

(This article belongs to the Topic Advanced Battery Thermal Management Solution for Electric Vehicles)

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18 pages, 7064 KiB

Open AccessReview

A Review on Advanced Battery Thermal Management Systems for Fast Charging in Electric Vehicles

by Le Duc Tai, Kunal Sandip Garud, Seong-Guk Hwang and Moo-Yeon Lee

Batteries 2024, 10(10), 372; https://doi.org/10.3390/batteries10100372 - 20 Oct 2024

Cited by 11 | Viewed by 8636

Abstract

To protect the environment and reduce dependence on fossil fuels, the world is shifting towards electric vehicles (EVs) as a sustainable solution. The development of fast charging technologies for EVs to reduce charging time and increase operating range is essential to replace traditional [...] Read more.

To protect the environment and reduce dependence on fossil fuels, the world is shifting towards electric vehicles (EVs) as a sustainable solution. The development of fast charging technologies for EVs to reduce charging time and increase operating range is essential to replace traditional internal combustion engine (ICE) vehicles. Lithium-ion batteries (LIBs) are efficient energy storage systems in EVs. However, the efficiency of LIBs depends significantly on their working temperature range. However, the huge amount of heat generated during fast charging increases battery temperature uncontrollably and may lead to thermal runaway, which poses serious hazards during the operation of EVs. In addition, fast charging with high current accelerates battery aging and seriously reduces battery capacity. Therefore, an effective and advanced battery thermal management system (BTMS) is essential to ensure the performance, lifetime, and safety of LIBs, particularly under extreme charging conditions. In this perspective, the current review presents the state-of-the-art thermal management strategies for LIBs during fast charging. The serious thermal problems owing to heat generated during fast charging and its impacts on LIBs are discussed. The core part of this review presents advanced cooling strategies such as indirect liquid cooling, immersion cooling, and hybrid cooling for the thermal management of batteries during fast charging based on recently published research studies in the period of 2019–2024 (5 years). Finally, the key findings and potential directions for next-generation BTMSs toward fast charging are proposed. This review offers an in-depth analysis by providing recommendations and potential solutions to develop reliable and efficient BTMSs for LIBs during fast charging. Full article

(This article belongs to the Special Issue Advances in Thermal Management for Batteries)

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16 pages, 1133 KiB

Open AccessArticle

The Role of Machine Learning in Enhancing Battery Management for Drone Operations: A Focus on SoH Prediction Using Ensemble Learning Techniques

by Büşra Çetinus, Saadin Oyucu, Ahmet Aksöz and Emre Biçer

Batteries 2024, 10(10), 371; https://doi.org/10.3390/batteries10100371 - 18 Oct 2024

Cited by 2 | Viewed by 1873

Abstract

This study considers the significance of drones in various civilian applications, emphasizing battery-operated drones and their advantages and limitations, and highlights the importance of energy consumption, battery capacity, and the state of health of batteries in ensuring efficient drone operation and endurance. It [...] Read more.

This study considers the significance of drones in various civilian applications, emphasizing battery-operated drones and their advantages and limitations, and highlights the importance of energy consumption, battery capacity, and the state of health of batteries in ensuring efficient drone operation and endurance. It also describes a robust testing methodology used to determine battery SoH accurately, considering discharge rates and using machine learning algorithms for analysis. Machine learning techniques, including classical regression models and Ensemble Learning methods, were developed and calibrated using experimental UAV data to predict SoH accurately. Evaluation metrics such as Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) assess model performance, highlighting the balance between model complexity and generalization. The results demonstrated improved SoH predictions with machine learning models, though complexities may lead to overfitting challenges. The transition from simpler regression models to intricate Ensemble Learning methods is meticulously described, including an assessment of each model’s strengths and limitations. Among the Ensemble Learning methods, Bagging, GBR, XGBoost, LightGBM, and stacking were studied. The stacking technique demonstrated promising results: for Flight 92 an RMSE of 0.03% and an MAE of 1.64% were observed, while for Flight 129 the RMSE was 0.66% and the MAE stood at 1.46%. Full article

(This article belongs to the Special Issue Machine Learning for Advanced Battery Systems)

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35 pages, 17707 KiB

Open AccessReview

Safety Aspects of Sodium-Ion Batteries: Prospective Analysis from First Generation Towards More Advanced Systems

by Pempa Tshering Bhutia, Sylvie Grugeon, Asmae El Mejdoubi, Stéphane Laruelle and Guy Marlair

Batteries 2024, 10(10), 370; https://doi.org/10.3390/batteries10100370 - 17 Oct 2024

Cited by 4 | Viewed by 4814

Abstract

After an introductory reminder of safety concerns pertaining to early rechargeable battery technologies, this review discusses current understandings and challenges of advanced sodium-ion batteries. Sodium-ion technology is now being marketed by industrial promoters who are advocating its workable capacity, as well as its [...] Read more.

After an introductory reminder of safety concerns pertaining to early rechargeable battery technologies, this review discusses current understandings and challenges of advanced sodium-ion batteries. Sodium-ion technology is now being marketed by industrial promoters who are advocating its workable capacity, as well as its use of readily accessible and cheaper key cell components. Often claimed to be safer than lithium-ion cells, currently only limited scientifically sound safety assessments of sodium-ion cells have been performed. However, the predicted sodium-ion development roadmap reveals that significant variants of sodium-ion batteries have entered or will potentially enter the market soon. With recent experiences of lithium-ion battery failures, sodium-ion battery safety management will constitute a key aspect of successful market penetration. As such, this review discusses the safety issues of sodium-ion batteries, presenting a twofold innovative perspective: (i) in terms of comparison with the parent lithium-ion technology making use of the same working principle and similar flammable non-aqueous solvent basis, and (ii) anticipating the arrival of innovative sub-chemistries at least partially inspired from successive generations of lithium-ion cells. The authors hope that the analysis provided will assist concerned stakeholders in the quest for safe marketing of sodium-ion batteries. Full article

(This article belongs to the Section Battery Performance, Ageing, Reliability and Safety)

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13 pages, 4592 KiB

Open AccessArticle

Inkjet-Printed Silver Lithiophilic Sites on Copper Current Collectors: Tuning the Interfacial Electrochemistry for Anode-Free Lithium Batteries

by Seyedalireza Mirbagheri, Eugenio Gibertini and Luca Magagnin

Batteries 2024, 10(10), 369; https://doi.org/10.3390/batteries10100369 - 17 Oct 2024

Cited by 1 | Viewed by 1897

Abstract

Anode-free lithium batteries (AFLBs) present an opportunity to eliminate the need for conventional graphite electrodes or excess lithium–metal anodes, thus increasing the cell energy density and streamlining the manufacturing process. However, their attributed poor coulombic efficiency leads to rapid capacity decay, underscoring the [...] Read more.

Anode-free lithium batteries (AFLBs) present an opportunity to eliminate the need for conventional graphite electrodes or excess lithium–metal anodes, thus increasing the cell energy density and streamlining the manufacturing process. However, their attributed poor coulombic efficiency leads to rapid capacity decay, underscoring the importance of achieving stable plating and stripping of Li on the negative electrode for the success of this cell configuration. A promising approach is the utilization of lithiophilic coatings such as silver to mitigate the Li nucleation overpotential on the Cu current collector, thereby improving the process of Li plating/stripping. On the other hand, inkjet printing (IJP) emerges as a promising technique for electrode modification in the manufacturing process of lithium batteries, offering a fast and scalable technology capable of depositing both thin films and patterned structures. In this work, a Fujifilm Dimatix inkjet printer was used to deposit Ag sites on a Cu current collector, aiming to modulate the interfacial electrochemistry of the system. Samples were fabricated with varying areas of coverage and the electrochemical performance of the system was systematically evaluated from bare Cu (non-lithiophilic) to a designed pattern (partially lithiophilic) and the fully coated thin film case (lithiophilic). Increasing lithiophilicity resulted in lower charge transfer resistance, higher exchange current density and reduced Li nucleation overpotential (from 55.75 mV for bare Cu to 13.5 mV for the fully coated case). Enhanced half-cell cyclability and higher coulombic efficiency were also achieved (91.22% CE over 76 cycles for bare Cu, 97.01% CE over 250 cycles for the fully coated case), alongside more uniform lithium deposition and fewer macroscopic irregularities. Moreover, our observations demonstrated that surface patterning through inkjet printing could represent an innovative, easy and scalable strategy to provide preferential Li nucleation sites to guide the subsequent Li deposition. Full article

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

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12 pages, 6221 KiB

Open AccessArticle

An Electrochemical Impedance Spectrum-Based State of Health Differential Indicator with Reduced Sensitivity to Measurement Errors for Lithium–Ion Batteries

by Jaber Abu Qahouq

Batteries 2024, 10(10), 368; https://doi.org/10.3390/batteries10100368 - 16 Oct 2024

Cited by 4 | Viewed by 1759

Abstract

As the use of electrochemical batteries, especially lithium–ion (Li-Ion) batteries, increases due to emerging applications and expanding markets, the accurate and fast estimation of their state of health (SOH) is becoming increasingly important. The accuracy of the SOH estimation is highly dependent on [...] Read more.

As the use of electrochemical batteries, especially lithium–ion (Li-Ion) batteries, increases due to emerging applications and expanding markets, the accurate and fast estimation of their state of health (SOH) is becoming increasingly important. The accuracy of the SOH estimation is highly dependent on the correlation strength between the used indicator and SOH and the accuracy of the SOH indicator measurement. This paper presents a new differential indicator which has a strong and consistent correlation with the SOH of Li-Ion batteries, based on a new Electrochemical Impedance Spectrum (EIS) Phase–Magnitude relationship. It is shown in this paper that the EIS Phase–Magnitude relationship exhibits a phase-based differential impedance magnitude SOH indicator between a first-phase peak point and a last-phase valley point. Because of the differential nature of this SOH indicator and because the two impedance values are measured at a phase peak point and a valley phase point regardless of the phase absolute values, the effect of impedance measurement shift/offset (error) on SOH estimation is reduced. This supports the future development of more accurate and faster online and offline SOH estimation algorithms and systems that have a higher immunity to impedance measurement shift/offset (error). Furthermore, in this work, the EIS was measured for a lithium–ion battery that was down to a ~15% SOH, which was not only used to support the conclusions of this paper, but also helped in filling a gap in the literature for EIS data under deep/high degradation levels. Full article

(This article belongs to the Special Issue Toward Next-Generation Rechargeable Lithium-Ion Batteries: Current Status and Future Prospects)

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25 pages, 8971 KiB

Open AccessArticle

General Machine Learning Approaches for Lithium-Ion Battery Capacity Fade Compared to Empirical Models

by Quentin Mayemba, Gabriel Ducret, An Li, Rémy Mingant and Pascal Venet

Batteries 2024, 10(10), 367; https://doi.org/10.3390/batteries10100367 - 16 Oct 2024

Cited by 1 | Viewed by 2556

Abstract

Today’s growing demand for lithium-ion batteries across various industrial sectors has introduced a new concern: battery aging. This issue necessitates the development of tools and models that can accurately predict battery aging. This study proposes a general framework for constructing battery aging models [...] Read more.

Today’s growing demand for lithium-ion batteries across various industrial sectors has introduced a new concern: battery aging. This issue necessitates the development of tools and models that can accurately predict battery aging. This study proposes a general framework for constructing battery aging models using machine learning techniques and compares these models with two existing empirical models, including a commercial one. To build the models, the databases produced by EVERLASTING and Bills et al. were utilized. The aim is to create universally applicable models that can address any battery-aging scenario. In this study, three types of models were developed: a vanilla neural network, a neural network inspired by extreme learning machines, and an encoder coupled with a neural network. The inputs for these models are derived from established knowledge in battery science, allowing the models to capture aging effects across different use cases. The models were trained on cells subjected to specific aging conditions and they were tested on other cells from the same database that experienced different aging conditions. The results obtained during the test for the vanilla neural network showed an RMSE of 1.3% on the Bills et al. test data and an RMSE of 2.7% on the EVERLASTING data, demonstrating similar or superior performance compared to the empirical models and proving the ability of the models to capture battery aging. Full article

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

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16 pages, 3920 KiB

Open AccessArticle

Characterization of Lithium-Ion Battery Fire Emissions—Part 2: Particle Size Distributions and Emission Factors

by Matthew Claassen, Bjoern Bingham, Judith C. Chow, John G. Watson, Pengbo Chu, Yan Wang and Xiaoliang Wang

Batteries 2024, 10(10), 366; https://doi.org/10.3390/batteries10100366 - 16 Oct 2024

Cited by 8 | Viewed by 3367

Abstract

The lithium-ion battery (LIB) thermal runaway (TR) emits a wide size range of particles with diverse chemical compositions. When inhaled, these particles can cause serious adverse health effects. This study measured the size distributions of particles with diameters less than 10 µm released [...] Read more.

The lithium-ion battery (LIB) thermal runaway (TR) emits a wide size range of particles with diverse chemical compositions. When inhaled, these particles can cause serious adverse health effects. This study measured the size distributions of particles with diameters less than 10 µm released throughout the TR-driven combustion of cylindrical lithium iron phosphate (LFP) and pouch-style lithium cobalt oxide (LCO) LIB cells. The chemical composition of fine particles (PM_2.5) and some acidic gases were also characterized from filter samples. The emission factors of particle number and mass as well as chemical components were calculated. Particle number concentrations were dominated by those smaller than 500 nm with geometric number mean diameters below 130 nm. Mass concentrations were also dominated by smaller particles, with PM₁ particles making up 81–95% of the measured PM₁₀ mass. A significant amount of organic and elemental carbon, phosphate, and fluoride was released as PM_2.5 constituents. The emission factor of gaseous hydrogen fluoride was 10–81 mg/Wh, posing the most immediate danger to human health. The tested LFP cells had higher emission factors of particles and HF than the LCO cells. Full article

(This article belongs to the Special Issue Thermal Safety of Lithium Ion Batteries)

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12 pages, 1486 KiB

Open AccessArticle

Garnet-Type Zinc Hexacyanoferrates as Lithium, Sodium, and Potassium Solid Electrolytes

by Leonhard Karger, Saravanakumar Murugan, Liping Wang, Zhirong Zhao-Karger, Aleksandr Kondrakov, Florian Strauss and Torsten Brezesinski

Batteries 2024, 10(10), 365; https://doi.org/10.3390/batteries10100365 - 16 Oct 2024

Viewed by 1659

Abstract

Sodium-ion batteries offer an attractive alternative to lithium-based chemistries due to the lower cost and abundance of sodium compared to lithium. Using solid electrolytes instead of liquid ones in such batteries may help improve safety and energy density, but they need to combine [...] Read more.

Sodium-ion batteries offer an attractive alternative to lithium-based chemistries due to the lower cost and abundance of sodium compared to lithium. Using solid electrolytes instead of liquid ones in such batteries may help improve safety and energy density, but they need to combine easy processing with high stability toward the electrodes. Herein, we describe a new class of solid electrolytes that are accessible by room-temperature, aqueous synthesis. The materials exhibit a garnet-type zinc hexacyanoferrate framework with large diffusion channels for alkaline ions. Specifically, they show superionic behavior and allow for facile processing into pellets. We compare the structure, stability, and transport properties of lithium-, sodium-, and potassium-containing zinc hexacyanoferrates and find that Na₂Zn₃[Fe(CN)₆]₂ achieves the highest ionic conductivity of up to 0.21 mS/cm at room temperature. In addition, the electrochemical performance and stability of the latter solid electrolyte are examined in solid-state sodium-ion batteries. Full article

(This article belongs to the Special Issue Advanced Electrode and Electrolyte Materials for All-Solid-State Batteries)

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18 pages, 36210 KiB

Open AccessArticle

Quantifying Lithium-Ion Battery Rate Capacity, Electrode Structuring, and Transport Phenomena Using E-I Measurements

by Ronan N. Dunne, Simon B. B. Solberg, Mahsid N. Amiri, Ejikeme Raphael Ezeigwe, Jacob J. Lamb and Odne Burheim

Batteries 2024, 10(10), 364; https://doi.org/10.3390/batteries10100364 - 15 Oct 2024

Viewed by 2246

Abstract

The specific energy of lithium-ion batteries (LIBs) can be enhanced through various approaches, one of which is increasing the proportion of active materials by thickening the electrodes. However, this typically leads to the battery having lower performance at a high cycling rate, a [...] Read more.

The specific energy of lithium-ion batteries (LIBs) can be enhanced through various approaches, one of which is increasing the proportion of active materials by thickening the electrodes. However, this typically leads to the battery having lower performance at a high cycling rate, a phenomenon commonly known as rate capacity retention. One solution to this is perforating the electrode, by creating channels or corrugations in the active electrode material, either as holes or as channels. This is known to reduce the rate capacity retention effect, but in order to engineer this better, a simplified transport process analysis needs to be established. In this paper, we propose a classic electrochemical analysis based on voltage–charge cycling measurements in order to obtain a classical mass transport coefficient,

h_{m}

, that is further used as a main indicator for electrode design quality assessment. We also demonstrate theoretically and experimentally how the mass transfer coefficient,

h_{m}

, can be determined and how it changes as the electrode layer thickness increases, with and without electrode corrugations. Full article

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17 pages, 3966 KiB

Open AccessArticle

A Novel Paraffin Wax/Expanded Graphite/Bacterial Cellulose Powder Phase Change Materials for the Dependable Battery Safety Management

by Jiajun Zhao, Yin Chen, Yan Gong and Mingyi Chen

Batteries 2024, 10(10), 363; https://doi.org/10.3390/batteries10100363 - 13 Oct 2024

Cited by 3 | Viewed by 2342

Abstract

Although phase change materials (PCMs) exhibit effective performance in the thermal management of lithium-ion batteries (LIBs), their development is limited by low thermal conductivity and susceptibility to leakage during the solid–liquid phase transition. To address these challenges and enhance thermal management capabilities, this [...] Read more.

Although phase change materials (PCMs) exhibit effective performance in the thermal management of lithium-ion batteries (LIBs), their development is limited by low thermal conductivity and susceptibility to leakage during the solid–liquid phase transition. To address these challenges and enhance thermal management capabilities, this study introduces a novel composite phase change material (CPCM) synthesized by physically mixing paraffin (PA), expanded graphite (EG), and bacterial cellulose (BC). The thermal performance of CPCMs with varying BC proportions is evaluated, and their impact on temperature control in battery thermal management systems (BTMS) is assessed. The results show that the addition of EG and BC significantly improves the thermal conductivity of the CPCM, reaching a value of 1.39 W·m⁻¹·K⁻¹. This also enhances the uniformity of temperature distribution within the battery module and reduces CPCM leakage. By comparing temperature variations within the battery module under different operating conditions, it was found that the intricate network structure of the CPCM promotes uniform temperature distribution, effectively mitigating temperature rise. Consequently, the maximum temperature and maximum temperature difference within the battery module were maintained below 47 °C and 4 °C, respectively. Compared to a system without phase change material at a 3C discharge rate, the maximum cell temperature, maximum module temperature, and maximum temperature difference were reduced by 32.38%, 26.92%, and 34.94%, respectively. These findings provide valuable insights for the design and optimization of BTMS. Full article

(This article belongs to the Special Issue Thermal Safety of Lithium Ion Batteries—2nd Edition)

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12 pages, 6720 KiB

Open AccessArticle

Manipulating Electrolyte Interface Chemistry Enables High-Performance TiO₂ Anode for Sodium-Ion Batteries

by Qi Wang, Rui Zhang, Dan Sun, Haiyan Wang and Yougen Tang

Batteries 2024, 10(10), 362; https://doi.org/10.3390/batteries10100362 - 11 Oct 2024

Cited by 1 | Viewed by 1614

Abstract

Titanium dioxide (TiO₂) has emerged as a candidate anode material for sodium-ion batteries (SIBs). However, their applications still face challenges of poor rate performance and low initial coulomb efficiency (ICE), which are induced by the unstable solid-electrolyte interface (SEI) and sluggish [...] Read more.

Titanium dioxide (TiO₂) has emerged as a candidate anode material for sodium-ion batteries (SIBs). However, their applications still face challenges of poor rate performance and low initial coulomb efficiency (ICE), which are induced by the unstable solid-electrolyte interface (SEI) and sluggish Na⁺ diffusion kinetics in conventional ester-based electrolytes. Herein, inspired by the electrode/electrolyte interfacial chemistry, tetrahydrofuran (THF) is exploited to construct an advanced electrolyte and reveal the relationship between the improved electrochemical performance and the derived SEI film on TiO₂ anode. The robust and homogeneously distributed F-rich SEI film formed in THF electrolyte favors fast interfacial charge transfer dynamics and excellent interfacial stability. As a result, the THF electrolyte endows the TiO₂ anode with greatly improved ICE (64.5%), exceptional rate capabilities (186 mAh g⁻¹ at 5.0 A g⁻¹), and remarkable cycling stability. This study elucidates the control of interfacial chemistry by rational electrolyte design and offers insights into the development of high-performance and long-lifetime TiO₂ anode. Full article

(This article belongs to the Special Issue High-Performance Materials for Sodium-Ion Batteries: 2nd Edition)

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12 pages, 4509 KiB

Open AccessArticle

Effects of Storage Voltage upon Sodium-Ion Batteries

by Tengfei Song, Brij Kishore, Yazid Lakhdar, Lin Chen, Peter R. Slater and Emma Kendrick

Batteries 2024, 10(10), 361; https://doi.org/10.3390/batteries10100361 - 11 Oct 2024

Cited by 2 | Viewed by 3009

Abstract

Sodium-ion batteries (SIBs) are gaining attention as a safer, more cost-effective alternative to lithium-ion batteries (LIBs) due to their use of abundant and non-critical materials. A notable feature of SIBs is their ability to utilize aluminum current collectors, which are resistant to oxidation, [...] Read more.

Sodium-ion batteries (SIBs) are gaining attention as a safer, more cost-effective alternative to lithium-ion batteries (LIBs) due to their use of abundant and non-critical materials. A notable feature of SIBs is their ability to utilize aluminum current collectors, which are resistant to oxidation, allowing for safer storage at 0 V. However, the long-term impacts of such storage on their electrochemical performance remain poorly understood. This study systematically investigates how storage conditions at various states of charge (SOCs) affect open circuit voltage (OCV) decay, internal resistance, and post-storage cycling stability in two different Na-ion chemistries: Prussian white//hard carbon and layered oxide//hard carbon. Electrochemical Impedance Spectroscopy before and after storage shows a pronounced increase in internal resistance and a corresponding decline in cycling performance when SIBs are stored in a fully discharged state (0 V), particularly for layered oxide-based cells, illustrating the sensitivity of different SIB chemistries to storage conditions. Additionally, a novel reformation protocol is proposed that reactivates cell capacity by rebuilding the solid electrolyte interphase (SEI) layer, offering a recovery path after prolonged storage. These insights into the long-term storage effects on SIBs provide new guidelines for optimizing storage and transport conditions to minimize performance degradation, making them more viable for commercial applications. Full article

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12 pages, 3191 KiB

Open AccessArticle

Surfactant-Assisted NiCo₂S₄ for Redox Supercapacitors

by Mawuse Amedzo-Adore and Jeong-In Han

Batteries 2024, 10(10), 360; https://doi.org/10.3390/batteries10100360 - 11 Oct 2024

Viewed by 1480

Abstract

Until now, crystalline NiCo₂S₄ and its composites have demonstrated improved performance in supercapacitor applications compared to their oxide analogues due to their relatively higher electrical conductivity and multifaceted redox reaction. However, amorphous phase materials have recently shown promise in electrochemical [...] Read more.

Until now, crystalline NiCo₂S₄ and its composites have demonstrated improved performance in supercapacitor applications compared to their oxide analogues due to their relatively higher electrical conductivity and multifaceted redox reaction. However, amorphous phase materials have recently shown promise in electrochemical energy storage systems. This work reports on amorphous NiCo₂S₄ with the help of urea via the hydrothermal method. It was noted that urea not only aided the amorphous formation but also served as a nitrogen precursor. In comparison, amorphous NiCo₂S₄ demonstrated a higher nitrogen atom% of 5.9 compared to 4.49 for crystalline NiCo₂S₄. Furthermore, the amorphous NiCo₂S₄ electrode exhibited superior electrochemical performance, with a specific capacitance of ~3506 F g⁻¹, which was higher than the cNCS electrode’s specific capacitance of ~2185 F g⁻¹ at 2 A g⁻¹. Additionally, aNCS in a two-electrode asymmetric supercapacitor exhibited a specific capacitance and an energy density of ~196 F g⁻¹ and 56 Wh kg⁻¹, respectively. Full article

(This article belongs to the Special Issue High Energy Density Supercapacitors: Acquisition, Characterization, and Application)

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10 pages, 6285 KiB

Open AccessArticle

Si₃N₄-Assisted Densification Sintering of Na₃Zr₂Si₂PO₁₂ Ceramic Electrolyte toward Solid-State Sodium Metal Batteries

by Wenwen Sun, Yang Li, Chen Sun, Zheng Sun, Haibo Jin and Yongjie Zhao

Batteries 2024, 10(10), 359; https://doi.org/10.3390/batteries10100359 - 11 Oct 2024

Viewed by 1494

Abstract

The solid-state metal battery with solid-state electrolytes has been considered the next generation of energy storage technology owing to its superior safety and high energy density. But, unfavorable ionic conductivity and interfacial problems make it difficult to widely use in practice. In this [...] Read more.

The solid-state metal battery with solid-state electrolytes has been considered the next generation of energy storage technology owing to its superior safety and high energy density. But, unfavorable ionic conductivity and interfacial problems make it difficult to widely use in practice. In this work, Si₃N₄ was rationally introduced into the NASICON matrix as a sintering aid, and the influence of Si₃N₄ on the crystal phase, microstructure, electrochemical and electrical performance of Na₃Zr₂Si₂PO₁₂ (NZSP) ceramic was systematically studied. The results demonstrate that the introduction of Si₃N₄ can effectively lower the densification sintering temperature of Na₃Zr₂Si₂PO₁₂ electrolyte and enhance the room temperature ionic conductivity of the NZSP to 3.82 × 10⁻⁴ S cm⁻¹. In addition, since Si₃N₄ has a high thermal conductivity and can inhibit the transmission of electrons between the grains of the electrolyte matrix, it will effectively hinder the generation of sodium metal dendrites and relieve the concentration of the heat source. Moreover, owing to the desirable interface compatibility of the Na and NZSP-Si₃N₄ electrolyte, the Na/NZSP-1150-1%Si₃N₄/Na symmetric battery exhibits excellent stability, and the electrode/electrolyte interface still maintains good integrity even after long-term cycling. The assembled Na/NZSP-1150-1%Si₃N₄/Na_3.5V_0.5Mn_0.5Fe_0.5Ti_0.5(PO₄)₃ cell manifests an initial specific capacity of 152.5 mA h g⁻¹, together with an initial Coulombic efficiency of 99.8%. Furthermore, after 200 cycles, the battery displays a capacity retention rate of 82%. Full article

(This article belongs to the Special Issue Electrolytes for Solid State Batteries—2nd Edition)

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23 pages, 5722 KiB

Open AccessArticle

Optimizing Energy Management and Sizing of Photovoltaic Batteries for a Household in Granada, Spain: A Novel Approach Considering Time Resolution

by Catalina Rus-Casas, Carlos Gilabert-Torres and Juan Ignacio Fernández-Carrasco

Batteries 2024, 10(10), 358; https://doi.org/10.3390/batteries10100358 - 11 Oct 2024

Cited by 5 | Viewed by 2241

Abstract

As residential adoption of renewable energy sources increases, optimizing rooftop photovoltaic systems (RTPVs) with Battery Energy Storage Systems (BESSs) is key for enhancing self-sufficiency and reducing dependence on the grid. This study introduces a novel methodology for sizing Home Energy Management Systems (HEMS), [...] Read more.

As residential adoption of renewable energy sources increases, optimizing rooftop photovoltaic systems (RTPVs) with Battery Energy Storage Systems (BESSs) is key for enhancing self-sufficiency and reducing dependence on the grid. This study introduces a novel methodology for sizing Home Energy Management Systems (HEMS), with the objective of minimizing the cost of imported energy while accounting for battery degradation. The battery model integrated nonlinear degradation effects and was evaluated in a real case study, considering different temporal data resolutions and various energy management strategies. For BESS capacities ranging from 1 to 5 kWh, the economic analysis demonstrated cost-effectiveness, with a Net Present Value (NPV) ranging from 54.53 € to 181.40 € and discounted payback periods (DPBs) between 6 and 10 years. The proposed HEMS extended battery lifespan by 22.47% and improved profitability by 21.29% compared to the current HEMS when applied to a 10 kWh BESS. Sensitivity analysis indicated that using a 5 min resolution could reduce NPV by up to 184.68% and increase DPB by up to 43.12% compared to a 60 min resolution for batteries between 1 and 5 kWh. This underscores the critical impact of temporal resolution on BESS sizing and highlights the need to balance accuracy with computational efficiency. Full article

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

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14 pages, 7065 KiB

Open AccessArticle

Sustainable Synthesis of a Carbon-Supported Magnetite Nanocomposite Anode Material for Lithium-Ion Batteries

by Hui Zeng, Jiahui Li, Haoyu Yin, Ruixin Jia, Longbiao Yu, Hongliang Li and Binghui Xu

Batteries 2024, 10(10), 357; https://doi.org/10.3390/batteries10100357 - 11 Oct 2024

Cited by 1 | Viewed by 1697

Abstract

Transition metal oxide magnetite (Fe₃O₄) is recognized as a potential anode material for lithium-ion batteries owing to its high theoretical specific capacity, modest voltage output, and eco-friendly character. It is a challenging task to engineer high-performance composite materials by [...] Read more.

Transition metal oxide magnetite (Fe₃O₄) is recognized as a potential anode material for lithium-ion batteries owing to its high theoretical specific capacity, modest voltage output, and eco-friendly character. It is a challenging task to engineer high-performance composite materials by effectively dispersing Fe₃O₄ crystals with limited sizes in a well-designed supporting framework following sustainable approaches. In this work, the naturally abundant plant products sodium lignosulfonate (Lig) and sodium cellulose (CMC) were selected to coprecipitate with Fe³⁺ ions under mild hydrothermal conditions. The Fe-Lig/CMC intermediate sediment with an optimized microstructure can be directly converted to the Lig/CMC-derived carbon matrix-supported Fe₃O₄ nanocomposite sample (Fe₃O₄@LigC/CC). Compared with the controlled Fe₃O₄@LigC material, the Fe₃O₄@LigC/CC nanocomposite provides superior electrochemical performance in the anode, which has inspiring specific capacities of 820.6 mAh g⁻¹ after 100 cycles under a current rate of 100 mA·g⁻¹ and 750.5 mAh g⁻¹ after 250 cycles, as well as more exciting rate capabilities. The biomimetic sample design and synthesis protocol closely follow the criteria of green chemistry and can be further developed in wider scenarios. Full article

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

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40 pages, 574 KiB

Open AccessReview

Evaluation of Advances in Battery Health Prediction for Electric Vehicles from Traditional Linear Filters to Latest Machine Learning Approaches

by Adrienn Dineva

Batteries 2024, 10(10), 356; https://doi.org/10.3390/batteries10100356 - 11 Oct 2024

Cited by 11 | Viewed by 4478

Abstract

In recent years, there has been growing interest in Li-ion battery State-of-Health (SOH) estimation due to its critical role in ensuring the safe and reliable operation of Electric Vehicles (EVs). Effective energy management and accurate SOH prediction are essential for the reliability and [...] Read more.

In recent years, there has been growing interest in Li-ion battery State-of-Health (SOH) estimation due to its critical role in ensuring the safe and reliable operation of Electric Vehicles (EVs). Effective energy management and accurate SOH prediction are essential for the reliability and sustainability of EVs. This paper presents an in-depth review of SOH estimation techniques, starting with an overview of seminal methods that lay the theoretical groundwork for battery modeling and SOH prediction. The review then evaluates recent advancements in Machine Learning (ML) and Artificial Intelligence (AI) techniques, emphasizing their contributions to improving SOH estimation. Through a rigorous screening process, the paper systematically assesses the evolution of these advanced methods, addressing specific research questions to evaluate their effectiveness and practical implications. Key findings highlight the potential of hybrid models that integrate Equivalent Circuit Models (ECMs) with Deep Learning approaches, offering enhanced accuracy and real-time performance. Additionally, the paper discusses limitations of current methods, such as challenges in translating laboratory-based models to real-world conditions and the computational complexity of some prospective methods. In conclusion, this paper identifies promising future research directions aimed at optimizing hybrid models and overcoming existing constraints to advance SOH estimation and battery management in Electric Vehicles. Full article

(This article belongs to the Special Issue State-of-Health Estimation of Batteries)

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18 pages, 6199 KiB

Open AccessArticle

In Operando Health Monitoring for Lithium-Ion Batteries in Electric Propulsion Using Deep Learning

by Jaya Vikeswara Rao Vajja, Alexey Serov, Meghana Sudarshan, Mahavir Singh and Vikas Tomar

Batteries 2024, 10(10), 355; https://doi.org/10.3390/batteries10100355 - 11 Oct 2024

Cited by 1 | Viewed by 1796

Abstract

Battery management systems (BMSs) play a vital role in understanding battery performance under extreme conditions such as high C-rate testing, where rapid charge or discharge is applied to batteries. This study presents a novel BMS tailored for continuous monitoring, transmission, and storage of [...] Read more.

Battery management systems (BMSs) play a vital role in understanding battery performance under extreme conditions such as high C-rate testing, where rapid charge or discharge is applied to batteries. This study presents a novel BMS tailored for continuous monitoring, transmission, and storage of essential parameters such as voltage, current, and temperature in an NCA 18650 4S lithium-ion battery (LIB) pack during high C-rate testing. By incorporating deep learning, our BMS monitors external battery parameters and predicts LIB’s health in terms of discharge capacity. Two experiments were conducted: a static experiment to validate the functionality of BMS, and an in operando experiment on an electrically propelled vehicle to assess real-world performance under high C-rate abuse testing with vibration. It was found that the external surface temperatures peaked at 55 °C during in operando flight, which was higher than that during static testing. During testing, the deep learning capacity estimation algorithm detected a mean capacity deviation of 0.04 Ah, showing an accurate state of health (SOH) by predicting the capacity of the battery. Our BMS demonstrated effective data collection and predictive capabilities, mirroring real-world conditions during abuse testing. Full article

(This article belongs to the Special Issue Artificial Intelligence and Batteries: AI-Powered Innovations in Battery Technology)

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21 pages, 3878 KiB

Open AccessArticle

Impact of Laser Ablation Strategies on Electrochemical Performances of 3D Batteries Containing Aqueous Acid Processed Li(Ni_0.6Mn_0.2Co_0.2)O₂ Cathodes with High Mass Loading

by Penghui Zhu, Yannic Sterzl and Wilhelm Pfleging

Batteries 2024, 10(10), 354; https://doi.org/10.3390/batteries10100354 - 10 Oct 2024

Cited by 1 | Viewed by 2006

Abstract

Lithium-ion batteries are currently one of the most important energy storage devices for various applications. However, it remains a great challenge to achieve both high energy density and high-power density while reducing the production costs. Cells with three-dimensional electrodes realized by laser ablation [...] Read more.

Lithium-ion batteries are currently one of the most important energy storage devices for various applications. However, it remains a great challenge to achieve both high energy density and high-power density while reducing the production costs. Cells with three-dimensional electrodes realized by laser ablation are proven to have enhanced electrochemical performance compared to those with conventional two-dimensional electrodes, especially at fast charging/discharging. Nevertheless, laser structuring of electrodes is still limited in terms of achievable processing speed, and the upscaling of the laser structuring process is of great importance to gain a high technology readiness level. In the presented research, the impact of different laser structuring strategies on the electro-chemical performance was investigated on aqueous processed Li(Ni₀.₆Mn₀.₂Co₀.₂)O₂ cathodes with acid addition during the slurry mixing process. Rate capability analyses of cells with laser structured aqueous processed electrodes exhibited enhanced performance with capacity increases of up to 60 mAh/g at high current density, while a 65% decrease in ionic resistance was observed for cells with laser structured electrodes. In addition, pouch cells with laser structured acid-added electrodes maintained 29–38% higher cell capacity after 500 cycles and their end-of-life was extended by a factor of about 4 in contrast to the reference cells with two-dimensional electrodes containing common organic solvent processed polyvinylidene fluoride binder. Full article

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16 pages, 5829 KiB

Open AccessArticle

Modelling of a Cylindrical Battery Mechanical Behavior under Compression Load

by Adrian Daniel Muresanu and Mircea Cristian Dudescu

Batteries 2024, 10(10), 353; https://doi.org/10.3390/batteries10100353 - 9 Oct 2024

Cited by 4 | Viewed by 2192

Abstract

The extensive utilization of lithium-ion (Li-ion) batteries within the automotive industry necessitates rigorous measures to ensure their mechanical robustness, crucial for averting thermal runaway incidents and ensuring vehicle safety. This paper introduces an innovative methodology aimed at homogenizing the mechanical response of Li-ion [...] Read more.

The extensive utilization of lithium-ion (Li-ion) batteries within the automotive industry necessitates rigorous measures to ensure their mechanical robustness, crucial for averting thermal runaway incidents and ensuring vehicle safety. This paper introduces an innovative methodology aimed at homogenizing the mechanical response of Li-ion batteries under compression load, using Finite Element Method (FEM) techniques to improve computational efficiency. A novel approach is proposed, involving the selective application of compression loads solely to the Jelly Roll and its casing, achieved by cutting the battery heads. Through this method, distinct mechanical behaviors are identified within the battery force displacement curve: an elastic region, a zone characterized by plastic deformation, and a segment exhibiting densification. By delineating these regions, our study facilitates a comprehensive understanding of the battery’s mechanical response under compression. Two battery models were employed in this study: one representing the battery as a solid volume, and another featuring the jelly roll as a solid volume enclosed by a shell representing the casing. The material utilized was LS Dyna MAT24, chosen for its piecewise characteristics’ definition, and its validation was primarily conducted through the curve fitting method applied to the force–displacement curve, taking in account the three regions of the compression force behavior. This approach not only optimizes computational resources but also offers insights crucial for enhancing the mechanical stability of Li-ion batteries in automotive applications. Full article

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

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15 pages, 4490 KiB

Open AccessArticle

Simulation of Dendrite Growth with a Diffusion-Limited Aggregation Model Validated by MRI of a Lithium Symmetric Cell during Charging

by Rok Peklar, Urša Mikac and Igor Serša

Batteries 2024, 10(10), 352; https://doi.org/10.3390/batteries10100352 - 8 Oct 2024

Cited by 1 | Viewed by 2407

Abstract

Lithium metal batteries offer high energy density but are challenged by dendrite growth, which can lead to short circuits and battery failure. Multiple models with varying degrees of accuracy and computational cost have been developed to understand and predict dendrite growth. This study [...] Read more.

Lithium metal batteries offer high energy density but are challenged by dendrite growth, which can lead to short circuits and battery failure. Multiple models with varying degrees of accuracy and computational cost have been developed to understand and predict dendrite growth. This study presents a simple model to simulate macroscale dendrite growth on lithium metal electrodes. The model uses a 3D single-particle Diffusion-Limited Aggregation (DLA) algorithm with an electric field bias to simulate dendrite growth. The electric field bias was introduced into the model with an important parameter, namely the biasing factor c, which determines the balance between diffusion and electric field effects. Before performing the simulation with the proposed model, the dendrite growth in a lithium symmetric cell during charging was measured by sequential 3D magnetic resonance imaging (MRI). These data were then used to validate the simulation, as the dendrite structure in each measured MRI time frame was used a starting point for a new simulation, the results of which were then validated with the measured dendrite structure of the next time frame. The best agreement between the simulated and measured dendrite structures using the overlap and displacement of deposition sites metrics was obtained at the biasing factor c = 0.7. This agreement was also good in terms with the fractal dimension of the dendrite structures. The proposed method offers a simple, accurate, and scalable framework for predicting dendrite growth over long deposition periods, making it a valuable tool for studying dendrite suppression under real-world battery charging conditions. Full article

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

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13 pages, 10800 KiB

Open AccessArticle

On the Stability of the Interface between Li₂TiS₃ Cathode and Li₆PS₅Cl Solid State Electrolytes for Battery Applications: A DFT Study

by Riccardo Rocca, Naiara Leticia Marana, Fabrizio Silveri, Maddalena D’Amore, Eleonora Ascrizzi, Mauro Francesco Sgroi, Nello Li Pira and Anna Maria Ferrari

Batteries 2024, 10(10), 351; https://doi.org/10.3390/batteries10100351 - 7 Oct 2024

Viewed by 1643

Abstract

Lithium-titanium-sulfur cathodes have garnered interest due to their distinctive properties and potential applications in lithium-ion batteries. They present various benefits, including lower cost, enhanced safety, and greater energy density compared to the commonly used transition metal oxides. The current trend in lithium-ion batteries [...] Read more.

Lithium-titanium-sulfur cathodes have garnered interest due to their distinctive properties and potential applications in lithium-ion batteries. They present various benefits, including lower cost, enhanced safety, and greater energy density compared to the commonly used transition metal oxides. The current trend in lithium-ion batteries is to move to all-solid-state chemistries in order to improve safety and energy density. Several chemistries for solid electrolytes have been studied, tested, and characterized to evaluate the applicability in energy storage system. Among those, sulfur-based Argyrodites have been coupled with cubic rock-salt type Li₂TiS₃ electrodes. In this work, Li₂TiS₃ surfaces were investigated with DFT methods in different conditions, covering the possible configurations that can occur during the cathode usage: pristine, delithiated, and overlithiated. Interfaces were built by coupling selected Li₂TiS₃ surfaces with the most stable Argyrodite surface, as derived from a previous study, allowing us to understand the (electro)chemical compatibility between these two sulfur-based materials. Full article

(This article belongs to the Special Issue Recent Process of Solid State Lithium Batteries)

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17 pages, 4486 KiB

Open AccessArticle

A Data-Driven Online Prediction Model for Battery Charging Efficiency Accounting for Entropic Heat

by Xiaowei Ding, Weige Zhang, Chenyang Yuan, Chang Ge, Yan Bao, Zhenjia An, Qiang Liu, Zhenpo Wang, Jinkai Shi and Zhihao Wang

Batteries 2024, 10(10), 350; https://doi.org/10.3390/batteries10100350 - 2 Oct 2024

Cited by 1 | Viewed by 1515

Abstract

This study proposes a charging efficiency calculation model based on an equivalent internal resistance framework. A data-driven neural network model is developed to predict the charging efficiency of lithium titanate (LTO) batteries for 5% state of charge (SOC) segments under various charging conditions. [...] Read more.

This study proposes a charging efficiency calculation model based on an equivalent internal resistance framework. A data-driven neural network model is developed to predict the charging efficiency of lithium titanate (LTO) batteries for 5% state of charge (SOC) segments under various charging conditions. By considering the impact of entropy change on the open-circuit voltage (OCV) during the charging process, the accuracy of energy efficiency calculations is improved. Incorporating battery data under various charging conditions, and comparing the predictive accuracy and computational complexity of different hyperparameter configurations, we establish a backpropagation neural network model designed for implementation in embedded systems. The model predicts the energy efficiency of subsequent 5% SOC segments based on the current SOC and operating conditions. The results indicate that the model achieves a prediction error of only 0.29% under unknown charging conditions while also facilitating the deployment of the neural network model in embedded systems. In future applications, the relevant predictive data can be transmitted in real time to the cooling system for thermal generation forecasting and predictive control of battery systems, thereby enhancing temperature control precision and improving cooling system efficiency. Full article

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

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13 pages, 5888 KiB

Open AccessArticle

Operando Fabricated Quasi-Solid-State Electrolyte Hinders Polysulfide Shuttles in an Advanced Li-S Battery

by Sayan Das, Krish Naresh Gupta, Austin Choi and Vilas Pol

Batteries 2024, 10(10), 349; https://doi.org/10.3390/batteries10100349 - 1 Oct 2024

Cited by 1 | Viewed by 2493

Abstract

Lithium-sulfur (Li-S) batteries are a promising option for energy storage due to their theoretical high energy density and the use of abundant, low-cost sulfur cathodes. Nevertheless, several obstacles remain, including the dissolution of lithium polysulfides (LiPS) into the electrolyte and a restricted operational [...] Read more.

Lithium-sulfur (Li-S) batteries are a promising option for energy storage due to their theoretical high energy density and the use of abundant, low-cost sulfur cathodes. Nevertheless, several obstacles remain, including the dissolution of lithium polysulfides (LiPS) into the electrolyte and a restricted operational temperature range. This manuscript presents a promising approach to addressing these challenges. The manuscript describes a straightforward and scalable in situ thermal polymerization method for synthesizing a quasi-solid-state electrolyte (QSE) by gelling pentaerythritol tetraacrylate (PETEA), azobisisobutyronitrile (AIBN), and a dual salt lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) and lithium nitrate (LiNO₃)-based liquid electrolyte. The resulting freestanding quasi-solid-state electrolyte (QSE) effectively inhibits the polysulfide shuttle effect across a wider temperature range of −25 °C to 45 °C. The electrolyte’s ability to prevent LiPS migration and cluster formation has been corroborated by scanning electron microscopy (SEM) and Raman spectroscopy analyses. The optimized QSE composition appears to act as a physical barrier, thereby significantly improving battery performance. Notably, the capacity retention has been demonstrated to reach 95% after 100 cycles at a 2C rate. Furthermore, the simple and scalable synthesis process paves the way for the potential commercialization of this technology. Full article

(This article belongs to the Special Issue Electrolytes for Solid State Batteries—2nd Edition)

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16 pages, 4071 KiB

Open AccessArticle

Improving the Performance of LiFePO₄ Cathodes with a Sulfur-Modified Carbon Layer

by Su-hyun Kwak and Yong Joon Park

Batteries 2024, 10(10), 348; https://doi.org/10.3390/batteries10100348 - 1 Oct 2024

Cited by 4 | Viewed by 2495

Abstract

LiFePO₄ (LFP) cathodes are popular due to their safety and cyclic performance, despite limitations in lithium-ion diffusion and conductivity. These can be improved with carbon coating, but further advancements are possible despite commercial success. In this study, we modified the carbon coating layer [...] Read more.

LiFePO₄ (LFP) cathodes are popular due to their safety and cyclic performance, despite limitations in lithium-ion diffusion and conductivity. These can be improved with carbon coating, but further advancements are possible despite commercial success. In this study, we modified the carbon coating layer using sulfur to enhance the electronic conductivity and stabilize the carbon surface layer via two methods: 1-step and 2-step processes. In the 1-step process, sulfur powder was mixed with cellulose followed by heat treatment to form a coating layer; in the 2-step process, an additional coating layer was applied on top of the carbon coating layer. Electrochemical measurements demonstrated that the 1-step sulfur-modified LFP significantly improved the discharge capacity (~152 mAh·g⁻¹ at 0.5 C rate) and rate capability compared to pristine LFP. Raman analyses indicated that sulfur mixed with a carbon source increases the graphitization of the carbon layer. Although the 2-step sulfur modification did not exceed the 1-step process in enhancing rate capability, it improved the storage characteristics of LFP at high temperatures. The residual sulfur elements apparently protected the surface. These findings confirm that sulfur modification of the carbon layer is effective for improving LFP cathode properties, offering a promising approach to enhance the performance and stability of LFP-based lithium-ion batteries. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries: Design, Preparation, Reaction Mechanisms of Electrode Materials, and Battery Life Evaluation)

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28 pages, 17826 KiB

Open AccessArticle

A Comprehensive Flow–Mass–Thermal–Electrochemical Coupling Model for a VRFB Stack and Its Application in a Stack Temperature Control Strategy

by Chen Yin, Mengyue Lu, Qiang Ma, Huaneng Su, Weiwei Yang and Qian Xu

Batteries 2024, 10(10), 347; https://doi.org/10.3390/batteries10100347 - 28 Sep 2024

Cited by 1 | Viewed by 1441

Abstract

In this work, a comprehensive multi-physics electrochemical hybrid stack model is developed for a vanadium redox flow battery (VRFB) stack considering electrolyte flow, mass transport, electrochemical reactions, shunt currents, and as heat generation and transfer simultaneously. Compared with other VRFB stack models, this [...] Read more.

In this work, a comprehensive multi-physics electrochemical hybrid stack model is developed for a vanadium redox flow battery (VRFB) stack considering electrolyte flow, mass transport, electrochemical reactions, shunt currents, and as heat generation and transfer simultaneously. Compared with other VRFB stack models, this model is more comprehensive in considering the influence of multiple factors. Based on the established model, the electrolyte flow rate distribution across cells in the stack is investigated. The distribution and variation in shunt currents, single-cell current and single-cell voltage are analyzed. The distribution and variation in temperature and heat generation and heat transfer are also researched. It can be found that the VRFB stack temperature will exceed 40 °C when operating at 60 A and 100 mA cm⁻² at an ambient temperature of 30 °C, which will lead to electrolyte ion precipitation, affecting the performance and safety of the battery. To control the stack temperature below 40 °C, a new tank cooling control strategy is proposed, and the suitable starting cooling point and the controlled temperature are specified. Compared with the common room cooling strategy, the new tank cooling strategy reduces energy consumption by 27.18% during 20 charge–discharge cycles. Full article

(This article belongs to the Special Issue Redox Flow Batteries and Hydrogen Technologies for Large-Scale and Long-Duration Energy Storage Applications)

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11 pages, 2960 KiB

Open AccessArticle

Honeycomb-like N-Doped Carbon Matrix-Encapsulated Co_1−xS/Co(PO₃)₂ Heterostructures for Advanced Lithium-Ion Capacitors

by Yutao Liu, Xiaopeng Xie, Zhaojia Wu, Tao Wen, Fang Zhao, Hao He, Junfei Duan and Wen Wang

Batteries 2024, 10(10), 346; https://doi.org/10.3390/batteries10100346 - 27 Sep 2024

Viewed by 1406

Abstract

Lithium-ion capacitors (LICs) are emerging as promising hybrid energy storage devices that combine the high energy densities of lithium-ion batteries (LIBs) with high power densities of supercapacitors (SCs). Nevertheless, the development of LICs is hindered by the kinetic imbalances between battery-type anodes and [...] Read more.

Lithium-ion capacitors (LICs) are emerging as promising hybrid energy storage devices that combine the high energy densities of lithium-ion batteries (LIBs) with high power densities of supercapacitors (SCs). Nevertheless, the development of LICs is hindered by the kinetic imbalances between battery-type anodes and capacitor-type cathodes. To address this issue, honeycomb-like N-doped carbon matrices encapsulating Co_1−xS/Co(PO₃)₂ heterostructures were prepared using a simple chemical blowing-vulcanization process followed by phosphorylation treatment (Co_1−xS/Co(PO₃)₂@NC). The Co_1−xS/Co(PO₃)₂@NC features a unique heterostructure engineered within carbon honeycomb structures, which efficiently promotes charge transfer at the interfaces, alleviates the volume expansion of Co-based materials, and accelerates reaction kinetics. The optimal Co_1−xS/Co(PO₃)₂@NC composite demonstrates a stable reversible capacity of 371.8 mAh g⁻¹ after 800 cycles at 1 A g⁻¹, and exhibits an excellent rate performance of 242.9 mAh g⁻¹ even at 8 A g⁻¹, alongside enhanced pseudocapacitive behavior. The assembled Co_1−xS/Co(PO₃)₂@NC//AC LIC delivers a high energy density of 90.47 Wh kg⁻¹ (at 26.28 W kg⁻¹), a high power density of 504.94 W kg⁻¹ (at 38.31 Wh kg⁻¹), and a remarkable cyclic stablitiy of 86.3% retention after 5000 cycles. This research is expected to provide valuable insights into the design of conversion-type electrode materials for future energy storage applications. Full article

(This article belongs to the Special Issue Advanced Studies on High-Performance Metal-Ion Capacitors: Technologies, Systems and Applications)

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18 pages, 2715 KiB

Open AccessArticle

Enhanced Electrochemical Performance of Lithium Iron Phosphate Cathodes Using Plasma-Assisted Reduced Graphene Oxide Additives for Lithium-Ion Batteries

by Suk Jekal, Chan-Gyo Kim, Jiwon Kim, Ha-Yeong Kim, Yeon-Ryong Chu, Yoon-Ho Ra, Zambaga Otgonbayar and Chang-Min Yoon

Batteries 2024, 10(10), 345; https://doi.org/10.3390/batteries10100345 - 27 Sep 2024

Cited by 1 | Viewed by 2491

Abstract

One-dimensional lithium-ion transport channels in lithium iron phosphate (LFP) used as a cathode in lithium-ion batteries (LIBs) result in low electrical conductivity and reduced electrochemical performance. To overcome this limitation, three-dimensional plasma-treated reduced graphene oxide (rGO) was synthesized in this study and used [...] Read more.

One-dimensional lithium-ion transport channels in lithium iron phosphate (LFP) used as a cathode in lithium-ion batteries (LIBs) result in low electrical conductivity and reduced electrochemical performance. To overcome this limitation, three-dimensional plasma-treated reduced graphene oxide (rGO) was synthesized in this study and used as an additive for LFP in LIB cathodes. Graphene oxide was synthesized using Hummers’ method, followed by mixing with LFP, lyophilization, and plasma treatment to obtain LFP@rGO. The plasma treatment achieved the highest degree of reduction and porosity in rGO, creating ion transfer channels. The structure of LFP@rGO was verified through scanning electron microscopy (SEM) analysis, which demonstrated that incorporating 10.0 wt% of rGO into LFP resulted in successful coverage by the rGO layer, forming LFP@rGO-10. In half-cell tests, LFP@rGO-10 exhibited a specific capacity of 142.7 mAh g⁻¹ at the 1.0 C-rate, which is higher than that of LFP. The full-cell exhibited 86.8% capacity retention after 200 cycles, demonstrating the effectiveness of rGO in enhancing the performance of LFP as an LIB cathode material. The outstanding efficiency and performance of the LFP@rGO-10//graphite cell highlight the promising potential of rGO-modified LFP as a cathode material for high-performance LIBs, providing both increased capacity and stability. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries and Li-Ion Capacitors: From Fundamentals to Practical Applications: 2nd Edition)

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10 pages, 1009 KiB

Open AccessArticle

First Principles Study of the Phase Stability, the Li Ionic Diffusion, and the Conductivity of the Li₁₀Ge_xMo_1−xP₂S₁₂ of Superionic Conductors

by Yifang Wu, Yuanzhen Chen and Shaokun Chong

Batteries 2024, 10(10), 344; https://doi.org/10.3390/batteries10100344 - 27 Sep 2024

Cited by 1 | Viewed by 1383

Abstract

Using first-principles density functional theory (DFT) calculations and ab initio molecular dynamics (AIMD) simulations, we performed this study on the phase stability, the intrinsic redox stability, and the Li⁺ conductivity of Li₁₀Ge_xMo_1−xP₂S₁₂ (x [...] Read more.

Using first-principles density functional theory (DFT) calculations and ab initio molecular dynamics (AIMD) simulations, we performed this study on the phase stability, the intrinsic redox stability, and the Li⁺ conductivity of Li₁₀Ge_xMo_1−xP₂S₁₂ (x = 0~1) superionic conductors. Molybdenum (Mo) is expected to replace expensive germanium (Ge) to lower tmaterial costs, reduce sensitivity to ambient water and oxygen, and achieve acceptable Li⁺ conductivity. The ab initio first principle molecular dynamics simulations show that room-temperature Li⁺ conductivity is 1.12 mS·cm⁻¹ for the Li₁₀Ge_0.75Mo_0.25P₂S₁₂ compound, which is comparable to the theoretical value of 6.81 mS·cm⁻¹ and the experimental measured one of 12 mS·cm⁻¹ of the Li₁₀GeP₂S₁₂ (LGPS) structure. For Li₁₀Ge_xMo_1−xP₂S₁₂ (x = 0, 0.25, 0.5 and 1) compounds, the density of states and the projection fractional wave state density were calculated. It was found that when Ge atoms were partially replaced by Mo atoms, the band gap remained unchanged at 2.5 eV, but deep level defects appeared in Mo-substituted compounds. Fortunately, this deep level defect is difficult to ionize at room temperature, so it has no effect on the electronic conductivity of Mo substitute compounds, making Mo substitution a suitable solution for electrolyte materials. The projection fractional wave state density calculation shows that the covalent bond between Mo and S is stronger than that between Ge and S, which reduces the sensitivity of Mo-substituted compounds to water and oxygen contents in the air. In addition, the partial state density coincidence curve between Li and S elements disappears in the 25% Mo-substituted compound with energies of 4–5 eV, indicating that the Li₂S by-product is decreased. Full article

(This article belongs to the Special Issue Lithium-Ion Batteries: Design, Preparation, Reaction Mechanisms of Electrode Materials, and Battery Life Evaluation)

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