Batteries

8 pages, 1743 KiB

Open AccessCommunication

Improved Mechanistic Degradation Modes Modeling of Lithium and Sodium Plating

by David Beck, Agata Greszta, Alexander Roberts and Matthieu Dubarry

Batteries 2024, 10(12), 408; https://doi.org/10.3390/batteries10120408 - 21 Nov 2024

Lithium and sodium plating are inevitable when using negative electrodes with an electrochemical potential close to one of the charge carriers. Typical testing and modeling assume that plating occurs at 0 V when measured against the charge carrier. While this might be true [...] Read more.

Lithium and sodium plating are inevitable when using negative electrodes with an electrochemical potential close to one of the charge carriers. Typical testing and modeling assume that plating occurs at 0 V when measured against the charge carrier. While this might be true under thermodynamic equilibrium, this is not true outside of steady state. This has significant implications as, by taking this into account, the testing voltage window of negative electrodes could be extended to allow gathering data for more complete discharges at higher rates. Moreover, from a modeling standpoint, it could also allow us to more accurately predict plating initiation potentials dynamically. This work presents the preliminary results of the investigation of what parameters are influencing the plating potential and how to take them into account in testing and modeling. Full article

(This article belongs to the Special Issue Battery Prognostics and Health Management)

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Graphical abstract

9 pages, 5523 KiB

Open AccessArticle

Gravure-Printed Anodes Based on Hard Carbon for Sodium-Ion Batteries

by Maria Montanino, Claudia Paoletti, Anna De Girolamo Del Mauro and Giuliano Sico

Batteries 2024, 10(11), 407; https://doi.org/10.3390/batteries10110407 - 20 Nov 2024

Abstract

Printed batteries are increasingly being investigated for feeding small, wearable devices more and more involved in our daily lives, promoting the study of printing technologies. Among these, gravure is very attractive as a low-cost and low-waste production method for functional layers in different [...] Read more.

Printed batteries are increasingly being investigated for feeding small, wearable devices more and more involved in our daily lives, promoting the study of printing technologies. Among these, gravure is very attractive as a low-cost and low-waste production method for functional layers in different fields, such as energy, sensors, and biomedical, because it is easy to scale up industrially. Thanks to our research, the feasibility of gravure printing was recently proved for rechargeable lithium-ion batteries (LiBs) manufacturing. Such studies allowed the production of high-quality electrodes involving different active materials with high stability, reproducibility, and good performance. Going beyond lithium-based storage devices, our attention was devoted on the possibility of employing highly sustainable gravure printing for sodium-ion batteries (NaBs) manufacturing, following the trendy interest in sodium, which is more abundant, economical, and ecofriendly than lithium. Here a study on gravure printed anodes for sodium-ion batteries based on hard carbon as an active material is presented and discussed. Thanks to our methodology centered on the capillary number, a high printing quality anodic layer was produced providing typical electrochemical behavior and good performance. Such results are very innovative and relevant in the field of sodium-ion batteries and further demonstrate the high potential of gravure in printed battery manufacturing. Full article

(This article belongs to the Special Issue Electrolyte and Electrode Design for Next-Generation Rechargeable Batteries)

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15 pages, 3975 KiB

Open AccessArticle

Internal Temperature Estimation for Lithium-Ion Cells Based on a Layered Electro-Thermal Equivalent Circuit Model

by Wei Shi, Wei Li and Shusheng Xiong

Batteries 2024, 10(11), 406; https://doi.org/10.3390/batteries10110406 - 18 Nov 2024

Abstract

In the domain of Battery Management System (BMS) research, the precise acquisition and estimation of internal temperature distribution within lithium-ion cells is a significant challenge. The commercial viability precludes the use of internal temperature sensors, and existing methodologies for online estimation of internal [...] Read more.

In the domain of Battery Management System (BMS) research, the precise acquisition and estimation of internal temperature distribution within lithium-ion cells is a significant challenge. The commercial viability precludes the use of internal temperature sensors, and existing methodologies for online estimation of internal temperatures under various electrical loads are constrained by computational limitations and model accuracy. This study presents a layered electro-thermal equivalent circuit model (LETECM), developed by integrating a layered second-order fractional equivalent circuit model with a layered thermal equivalent circuit model. A lithium-ion battery divided into three layers was employed to illustrate the development of this LETECM. The model’s precision was validated against a 3D Newman Finite Element Model (3DNFEM), constructed using actual battery parameters. Given that the thermal gradient inside the battery is usually more pronounced under high load conditions, a 10C direct current discharge for 60 s followed by a rest period of 240 s was adopted as the test condition in the simulation. The results indicate that at the end of the DC discharge, the temperature difference between the inner layer and the surface of the battery was the largest and the maximum temperature difference predicted by the LETECM was 3.58 °C, while the 3DNFEM exhibited a temperature difference of 3.74 °C. The trends in each layer temperature and battery surface temperature obtained by the two models are highly consistent. The proposed model offers computational efficiency and maintains notable accuracy, suggesting its potential integration into BMS for real-time online applications. This advancement could provide critical internal temperature data for refining battery charging and discharging performance assessments and lifespan predictions, thereby optimizing battery management strategies. Full article

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10 pages, 2870 KiB

Open AccessArticle

Modulating Diffusion Double Layer by In Situ Constructed Ultrathin Dipole Layer Towards Uniform Lithium Deposition

by Yang Nan, Songmei Li, Wen Li, Guoke Wei and Bin Li

Batteries 2024, 10(11), 405; https://doi.org/10.3390/batteries10110405 - 18 Nov 2024

Abstract

The popularization of lithium metal anode has been limited due to uneven deposition processes and lithium dendrites. Guiding homogeneous nucleation during the initial plating stage of lithium is vital to obtain a stable lithium metal anode. Herein, an ultra-thin dipole layer that can [...] Read more.

The popularization of lithium metal anode has been limited due to uneven deposition processes and lithium dendrites. Guiding homogeneous nucleation during the initial plating stage of lithium is vital to obtain a stable lithium metal anode. Herein, an ultra-thin dipole layer that can be used to regulate the diffusion layer is prepared by anodizing and strong polarization on a titanium foil collector. It is demonstrated that the vertical distributions of ionic concentration and electrostatic potential on the nBTO@Ti electrode are modulated by the ultrathin dipole layer, leading to uniform diffusion of lithium ions and reduction of overpotential. Consequently, a uniform lithium nucleation and plating process are achieved on a polarized BaTiO₃ collector, which is verified by microscopy. The average coulombic efficiency of the deposition-dissolution process is as high as 98.3% for 300 cycles at 0.5 mA cm⁻². Moreover, the symmetrical cell shows flat potential platforms of 25 mV for 1000 cycles at 0.5 mA cm⁻². Full cell with LiFePO₄ as cathode also reveals excellent electrochemical performances with a steady discharge capacity of 120 mAh g⁻¹ at 1 C and a high capacity retention of 93.3% after 200 cycles. Full article

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14 pages, 651 KiB

Open AccessArticle

Coupled Electro-Thermal-Aging Battery Pack Modeling—Part 1: Cell Level

by Hadi Pasdarshahri, Émile Veilleux, William Mooney, Luc G. Fréchette, François Grondin and David Rancourt

Batteries 2024, 10(11), 404; https://doi.org/10.3390/batteries10110404 - 17 Nov 2024

Abstract

This paper presents a modeling approach to capture the coupled effects of electrical–thermal aging in Li-ion batteries at the cell level. The proposed semi-empirical method allows for a relatively high accuracy and low computational cost compared to expensive computer simulations. This is something [...] Read more.

This paper presents a modeling approach to capture the coupled effects of electrical–thermal aging in Li-ion batteries at the cell level. The proposed semi-empirical method allows for a relatively high accuracy and low computational cost compared to expensive computer simulations. This is something current models often lack but is essential for system level simulations, relevant for electric vehicle manufacturers. The aging analysis includes both cycling and calendar effects across the lifetime of the cell and reversible and irreversible heat in a lumped-mass model to capture the temperature evolution of the cell in operation. The Thévenin equivalent circuit model with capacitance used to simulate the electrical behavior of the cell was experimentally validated, showing a high correlation with the proposed model during the charging and discharging phases. A maximum error of 3% on the voltage reading was identified during discharge with the complete model. This model was also designed to be used as a stepping stone for a comprehensive model at the module and vehicle levels that can later be used by designers. Full article

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22 pages, 7572 KiB

Open AccessArticle

Assessment of a Top and Bottom Cooling Strategy for Prismatic Lithium-Ion Cells Intended for Automotive Use

by Said Madaoui, Bartlomiej Guzowski, Roman Gozdur, Zlatina Dimitrova, Nicolas Audiot, Jocelyn Sabatier, Jean-Michel Vinassa and Franck Guillemard

Batteries 2024, 10(11), 403; https://doi.org/10.3390/batteries10110403 - 15 Nov 2024

Abstract

In contemporary vehicle applications, lithium-ion batteries have become a leading option among the diverse array of battery technologies available. This preference is attributed to their advantageous properties, which include low self-discharge rates and no memory effect. Despite these benefits, lithium-ion batteries are not [...] Read more.

In contemporary vehicle applications, lithium-ion batteries have become a leading option among the diverse array of battery technologies available. This preference is attributed to their advantageous properties, which include low self-discharge rates and no memory effect. Despite these benefits, lithium-ion batteries are not without their challenges. The key issues include a restricted driving range, concerns regarding longevity, safety risks, and prolonged charging durations. Efforts aimed at minimizing the charging duration frequently entail the introduction of elevated currents into the battery, a practice that can significantly elevate its temperature and, in turn, diminish its operational lifespan. Generally, battery packs in electric vehicles are equipped with flat cooling plates located on their side or bottom surfaces, which also serve the dual purpose of providing heating in colder conditions. Nevertheless, this cooling configuration faces difficulties during fast charging and may not efficiently heat or cool the batteries. In this work, a novel thermal management approach is proposed, in which a battery module is cooled not only with a bottom cooling plate but also using another cooling plate in contact with the busbars, located on the top of the battery module. The simulations and experimental tests show that this new configuration demonstrates significant improvements. The thermal time constant is reduced by 47%, enabling faster cooling of the module. Additionally, the maximum temperature reached by the battery during charging with dual cooling is lowered by 6 °C compared to the conventional approach. In this configuration, the top cooling plate acts as a thermal bridge. This is a key advantage that promotes temperature homogenization within the battery module. As a result, it supports an even aging process of batteries, ensuring their longevity and optimal performance. Full article

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18 pages, 8024 KiB

Open AccessArticle

Evaluating a Nickel–Metal Hydride (NiMH) Battery Regeneration Patent Based on a Non-Intrusive and Unsupervised Prototype

by Rafael Martínez-Sánchez, Angel Molina-García, Antonio Mateo-Aroca and Alfonso P. Ramallo-González

Batteries 2024, 10(11), 402; https://doi.org/10.3390/batteries10110402 - 14 Nov 2024

Abstract

In the ongoing shift toward electric vehicles (EVs) primarily utilizing lithium-ion battery technology, a significant population of hybrid electric vehicles (HEVs) remains operational, which are reliant on established NiMH battery systems. Over the last twenty years, these HEVs have generated a substantial number [...] Read more.

In the ongoing shift toward electric vehicles (EVs) primarily utilizing lithium-ion battery technology, a significant population of hybrid electric vehicles (HEVs) remains operational, which are reliant on established NiMH battery systems. Over the last twenty years, these HEVs have generated a substantial number of NiMH batteries that are either inoperable, experiencing performance degradation, or approaching the end of their service life. This situation results in a twofold challenge: (i) a growing volume of environmentally hazardous waste due to the difficulty of NiMH battery reclamation and (ii) escalating maintenance costs for HEV owners necessitated by replacement battery purchases. To overcome this scenario, patent WO2015092107A1, published in 2015, proposed a ‘Method for regenerating NiMH batteries.’ This method claimed the ability to restore NiMH batteries to their original functionality based on a non-intrusive approach. However, a comprehensive review of the relevant scientific literature fails to identify any empirical evidence supporting the efficacy of this regeneration technique. Within this context, this study provides a detailed analysis and evaluation of the regeneration process based on an unsupervised and non-intrusive prototype. The proposed prototype can be used not only to implement and evaluate the previous patent, but also to test any other process or methodology based on controlled charging/discharging periods under certain current conditions. NiMH battery cells from a Toyota Prius were included in this work as a real case study. The experimental results from this prototype demonstrate the reduced potential for battery regeneration using the proposed method. Future contributions should offer a promising solution for mitigating the challenges associated with NiMH battery disposal, maintenance within the HEV domain, and other second-life alternative options. Full article

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15 pages, 3368 KiB

Open AccessArticle

The Role of Interfacial Effects in the Impedance of Nanostructured Solid Polymer Electrolytes

by Martino Airoldi, Ullrich Steiner and Ilja Gunkel

Batteries 2024, 10(11), 401; https://doi.org/10.3390/batteries10110401 - 12 Nov 2024

Abstract

The role of interfacial effects on an ion-conducting poly(styrene-b-ethylene oxide) (PS-b-PEO or SEO) diblock copolymer doped with lithium bis(trifluoromethanesulfonyl) imide (LiTFSI) was investigated by electrochemical impedance spectroscopy (EIS). Coating the surface of commonly used stainless steel electrodes with a [...] Read more.

The role of interfacial effects on an ion-conducting poly(styrene-b-ethylene oxide) (PS-b-PEO or SEO) diblock copolymer doped with lithium bis(trifluoromethanesulfonyl) imide (LiTFSI) was investigated by electrochemical impedance spectroscopy (EIS). Coating the surface of commonly used stainless steel electrodes with a specific random copolymer brush increases the measured ionic conductivity by more than an order of magnitude compared to the uncoated electrodes. The increase in ionic conductivity is related to the interfacial structure of the block copolymer domain morphology on the electrode surface. We show that the impedance associated with the electrode–electrolyte interface can be detected using nonmetallic electrodes, allowing us to distinguish the ionic conductivity behaviors of the bulk electrolyte and the interfacial layers for both as-prepared and annealed samples. Full article

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

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25 pages, 1385 KiB

Open AccessArticle

A Comparison of Battery Equivalent Circuit Model Parameter Extraction Approaches Based on Electrochemical Impedance Spectroscopy

by Yuchao Wu and Balakumar Balasingam

Batteries 2024, 10(11), 400; https://doi.org/10.3390/batteries10110400 - 10 Nov 2024

Abstract

This paper presents three approaches to estimating the battery parameters of the electrical equivalent circuit model (ECM) based on electrochemical impedance spectroscopy (EIS); these approaches are referred to as (a) least squares (LS), (b) exhaustive search (ES), and (c) nonlinear least squares (NLS). [...] Read more.

This paper presents three approaches to estimating the battery parameters of the electrical equivalent circuit model (ECM) based on electrochemical impedance spectroscopy (EIS); these approaches are referred to as (a) least squares (LS), (b) exhaustive search (ES), and (c) nonlinear least squares (NLS). The ES approach is assisted by the LS method for the rough determination of the lower and upper bound of the ECM parameters, and the NLS approach is incorporated with the Monte Carlo run such that different initial guesses can be assigned to improve the goodness of EIS fitting. The proposed approaches are validated using both simulated and real EIS data. Compared to the LS approach, the ES and NLS approaches show better fitting accuracy at various noise levels, whereas in both the validation using simulated EIS data and actual EIS data collected from LG 18650 and Molicel 21700 batteries, the NLS approach shows better fitting accuracy than that of LS and ES approaches. In all cases, compared with the ES approach, the computational time of the NLS approach is significantly faster, and compared with the LS approach, the NLS approach shows a minimal difference in computational time and considerably better fitting performance. Full article

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

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23 pages, 4462 KiB

Open AccessArticle

Prediction of Lithium-Ion Battery Health Using GRU-BPP

by Sahar Qaadan, Aiman Alshare, Alexander Popp and Benedikt Schmuelling

Batteries 2024, 10(11), 399; https://doi.org/10.3390/batteries10110399 - 8 Nov 2024

Abstract

Accurate prediction of lithium-ion batteries’ (LIBs) state-of-health (SOH) is crucial for the safety and maintenance of LIB-powered systems. This study addresses the variability in degradation trajectories by applying gated recurrent unit (GRU) networks alongside principal component analysis (PCA), Granger causality, and K-means clustering [...] Read more.

Accurate prediction of lithium-ion batteries’ (LIBs) state-of-health (SOH) is crucial for the safety and maintenance of LIB-powered systems. This study addresses the variability in degradation trajectories by applying gated recurrent unit (GRU) networks alongside principal component analysis (PCA), Granger causality, and K-means clustering to analyze the relationships between operating conditions—such as temperature and load profiles—and battery performance degradation. This paper uses a publicly accessible dataset derived by aging three prismatic LIB cells under a realistic forklift operation profile. First, we identify the features that are relevant to driving variance, then we employ the winning algorithm of K-means clustering for the classification of operational states. Granger causality later investigates the inter-group relationships. Our GRU-BPP model achieves an RMSE value of 0.167 and an MAE of 0.129 for the reference performance testing (RPT) dataset and an RMSE of 0.032 with an MAE of 0.025 for the aging dataset, thus outperformed benchmark methods such as GRU, LME, and XGBoost. These results further enhance the predictiveness and robustness of this approach and yield a holistic solution to the conventional challenges in battery management and their remaining useful life (RUL) predictions. Full article

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20 pages, 4412 KiB

Open AccessArticle

Prediction of Lithium-Ion Battery State of Health Using a Deep Hybrid Kernel Extreme Learning Machine Optimized by the Improved Black-Winged Kite Algorithm

by Juncheng Fu, Zhengxiang Song, Jinhao Meng and Chunling Wu

Batteries 2024, 10(11), 398; https://doi.org/10.3390/batteries10110398 - 8 Nov 2024

Abstract

The accurate prediction of lithium-ion battery state of health (SOH) can extend battery life, enhance device safety, and ensure sustained reliability in critical applications. Addressing the non-linear and non-stationary characteristics of battery capacity sequences, a novel method for predicting lithium battery SOH is [...] Read more.

The accurate prediction of lithium-ion battery state of health (SOH) can extend battery life, enhance device safety, and ensure sustained reliability in critical applications. Addressing the non-linear and non-stationary characteristics of battery capacity sequences, a novel method for predicting lithium battery SOH is proposed using a deep hybrid kernel extreme learning machine (DHKELM) optimized by the improved black-winged kite algorithm (IBKA). First, to address the limitations of traditional extreme learning machines (ELMs) in capturing non-linear features and their poor generalization ability, the concepts of auto encoders (AEs) and hybrid kernel functions are introduced to enhance ELM, resulting in the establishment of the DHKELM model for SOH prediction. Next, to tackle the challenge of parameter selection for DHKELM, an optimal point set strategy, the Gompertz growth model, and a Levy flight strategy are employed to optimize the parameters of DHKELM using IBKA before model training. Finally, the performance of IBKA-DHKELM is validated using two distinct datasets from NASA and CALCE, comparing it against ELM, DHKELM, and BKA-DHKELM. The results show that IBKA-DHKELM achieves the smallest error, with an RMSE of only 0.0062, demonstrating exceptional non-linear fitting capability, high predictive accuracy, and good robustness. Full article

(This article belongs to the Special Issue Control, Modelling, and Management of Batteries)

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14 pages, 11889 KiB

Open AccessArticle

Thermal Propagation Test Bench for the Study of the Paschen Curve and Lightning Arcs of Venting Gas

by Björn Mulder, Kai Peter Birke, Björn Obry, Stefan Wigger, Ruslan Kozakov, Pavel Smirnov and Jochen Schein

Batteries 2024, 10(11), 397; https://doi.org/10.3390/batteries10110397 - 8 Nov 2024

Abstract

Thermal propagation events are characterized by fire and thick black smoke, leading to propagation methods with a focus on preventing heat transfer and optimizing gas flow. Yet little attention is being paid to the electric conductivity of the gas, leading to possibly unexpected [...] Read more.

Thermal propagation events are characterized by fire and thick black smoke, leading to propagation methods with a focus on preventing heat transfer and optimizing gas flow. Yet little attention is being paid to the electric conductivity of the gas, leading to possibly unexpected battery casing openings due to lightning arcs as well as potentially providing the minimum ignition energy. This gas composition (omitting particles) was used at different temperatures and pressures in a lightning arc test bench, leading to the Paschen curve. Using a mini-module cell setup, filtered venting gas was flowed through another lightning arc test bench, allowing for in situ measurements. Full article

(This article belongs to the Special Issue Advances in Lithium-Ion Battery Safety and Fire)

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22 pages, 7929 KiB

Open AccessReview

Recent Advances in High-Performance Carbon-Based Electrodes for Zinc-Ion Hybrid Capacitors

by Ying Liu, Lechun Song, Chenze Li, Caicheng Song and Xiang Wu

Batteries 2024, 10(11), 396; https://doi.org/10.3390/batteries10110396 - 7 Nov 2024

Abstract

Aqueous zinc-ion hybrid capacitors (ZIHCs) have emerged as a promising technology, showing superior energy and power densities, as well as enhanced safety, inexpensive and eco-friendly features. Although ZIHCs possess the advantages of both batteries and supercapacitors, their energy density is still unsatisfactory. Therefore, [...] Read more.

Aqueous zinc-ion hybrid capacitors (ZIHCs) have emerged as a promising technology, showing superior energy and power densities, as well as enhanced safety, inexpensive and eco-friendly features. Although ZIHCs possess the advantages of both batteries and supercapacitors, their energy density is still unsatisfactory. Therefore, it is extremely crucial to develop reasonably matched electrode materials. Based on this challenge, a surge of studies has been conducted on the modification of carbon-based electrode materials. Herein, we first summarize the progress of the related research and elucidate the energy storage mechanism associated with carbon-based electrodes for ZIHCs. Then, we investigate the influence of the synthesis routes and modification strategies of the electrode materials on electrochemical stability. Finally, we summarize the current research challenges facing ZIHCs and predict potential future research pathways. In addition, we suggest key scientific questions to focus on and potential directions for further exploration. 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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25 pages, 5058 KiB

Open AccessReview

Research Progress and Challenges of Carbon/MXene Composites for Supercapacitors

by Li Sun, Yu Dong, Hangyu Li, Hanqi Meng, Jianfei Liu, Qigao Cao and Chunxu Pan

Batteries 2024, 10(11), 395; https://doi.org/10.3390/batteries10110395 - 7 Nov 2024

Abstract

Carbon materials/MXenes composite materials have gained widespread attention in the field of supercapacitors due to their excellent electrochemical performance. Carbon materials are considered ideal electrode materials for supercapacitors due to their high specific surface area, good conductivity, and outstanding electrochemical stability. MXenes, as [...] Read more.

Carbon materials/MXenes composite materials have gained widespread attention in the field of supercapacitors due to their excellent electrochemical performance. Carbon materials are considered ideal electrode materials for supercapacitors due to their high specific surface area, good conductivity, and outstanding electrochemical stability. MXenes, as a novel two-dimensional material, exhibit prominent conductivity, mechanical properties, and ionic conductivity, thereby showing great potential for applications in energy storage devices. The combination of carbon materials and MXenes is expected to fully leverage the advantages of both, optimizing electrode conductivity, enhancing the energy density and power density, and improving the charge–discharge performance. This article reviews the key research progress of carbon/MXenes composite materials in supercapacitors in recent years, including their synthesis methods, structural tuning, and improvements in their electrochemical performance. Finally, the article looks forward to future research directions and proposes potential strategies to enhance the overall performance of the composite materials and achieve large-scale applications. By addressing the existing challenges, carbon/MXenes composite materials are anticipated to achieve higher energy and power outputs for the supercapacitor field in the future, providing strong support for the development of new energy storage technologies such as electric vehicles and wearable devices. Full article

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

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22 pages, 11094 KiB

Open AccessArticle

State of Health Estimation for Lithium-Ion Batteries Using an Explainable XGBoost Model with Parameter Optimization

by Zhenghao Xiao, Bo Jiang, Jiangong Zhu, Xuezhe Wei and Haifeng Dai

Batteries 2024, 10(11), 394; https://doi.org/10.3390/batteries10110394 - 7 Nov 2024

Abstract

Accurate and reliable estimation of the state of health (SOH) of lithium-ion batteries is crucial for ensuring safety and preventing potential failures of power sources in electric vehicles. However, current data-driven SOH estimation methods face challenges related to adaptiveness and interpretability. This paper [...] Read more.

Accurate and reliable estimation of the state of health (SOH) of lithium-ion batteries is crucial for ensuring safety and preventing potential failures of power sources in electric vehicles. However, current data-driven SOH estimation methods face challenges related to adaptiveness and interpretability. This paper investigates an adaptive and explainable battery SOH estimation approach using the eXtreme Gradient Boosting (XGBoost) model. First, several battery health features extracted from various charging and relaxation processes are identified, and their correlation with battery aging is analyzed. Then, a SOH estimation method based on the XGBoost algorithm is established, and the model’s hyper-parameters are tuned using the Bayesian optimization algorithm (BOA) to enhance the adaptiveness of the proposed estimation model. Additionally, the Tree SHapley Additive exPlanation (TreeSHAP) technique is employed to analyze the explainability of the estimation model and reveal the influence of different features on SOH evaluation. Experiments involving two types of batteries under various aging conditions are conducted to obtain battery cycling aging data for model training and validation. The quantitative results demonstrate that the proposed method achieves an estimation accuracy with a mean absolute error of less than 2.7% and a root mean squared error of less than 3.2%. Moreover, the proposed method shows superior estimation accuracy and performance compared to existing machine learning models. Full article

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

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12 pages, 5238 KiB

Open AccessArticle

Simulation and Optimization of a Hybrid Photovoltaic/Li-Ion Battery System

by Xiaoxiao Yu, Juntao Fan, Zihua Wu, Haiping Hong, Huaqing Xie, Lan Dong and Yihuai Li

Batteries 2024, 10(11), 393; https://doi.org/10.3390/batteries10110393 - 6 Nov 2024

Abstract

The coupling of solar cells and Li-ion batteries is an efficient method of energy storage, but solar power suffers from the disadvantages of randomness, intermittency and fluctuation, which cause the low conversion efficiency from solar energy into electric energy. In this paper, a [...] Read more.

The coupling of solar cells and Li-ion batteries is an efficient method of energy storage, but solar power suffers from the disadvantages of randomness, intermittency and fluctuation, which cause the low conversion efficiency from solar energy into electric energy. In this paper, a circuit model for the coupling system with PV cells and a charge controller for a Li-ion battery is presented in the MATLAB/Simulink environment. A new three-stage charging strategy is proposed to explore the changing performance of the Li-ion battery, comprising constant-current charging, maximum power point tracker (MPPT) charging and constant-voltage charging stages, among which the MPPT charging stage can achieve the fastest maximum power point (MPP) capture and, therefore, improve battery charging efficiency. Furthermore, the charge controller can improve the lifetime of the battery through the constant-current and constant-voltage charging scheme. The simulation results indicate that the three-stage charging strategy can achieve an improvement in the maximum power tracking efficiency of 99.9%, and the average charge controller efficiency can reach 96.25%, which is higher than that of commercial chargers. This work efficiently matches PV cells and Li-ion batteries to enhance solar energy storages, and provides a new optimization idea for hybrid PV/Li-ion systems. 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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29 pages, 1273 KiB

Open AccessArticle

Model-Based Performance Evaluation of Hybrid Solid-State Batteries: Impact of Laser-Ablated Geometrical Structures

by Maximilian Scheller, Axel Durdel, Alexander Frank and Andreas Jossen

Batteries 2024, 10(11), 392; https://doi.org/10.3390/batteries10110392 - 5 Nov 2024

Abstract

Due to challenges in manufacturing composite cathodes with oxide solid electrolytes, new cell concepts are emerging in which the infiltration of solid-polymer electrolyte (SPE) into 3D cathode pore structures improves capacity retention and cycling stability. However, the performance limitation and the resulting practical [...] Read more.

Due to challenges in manufacturing composite cathodes with oxide solid electrolytes, new cell concepts are emerging in which the infiltration of solid-polymer electrolyte (SPE) into 3D cathode pore structures improves capacity retention and cycling stability. However, the performance limitation and the resulting practical relevance of such a hybrid concept have not yet been analyzed and discussed. This study investigates the impact of laser-ablated geometric structures on the performance of hybrid solid-state batteries (SSBs). A Doyle–Fuller–Newman modeling approach is developed and parameterized for structured hybrid SSBs that incorporate a PEO/LiTFSI SPE and an LLZO ceramic separator, as well as NMC-811 and Li-metal for the positive- and negative-electrode active materials. Comparison between structured and planar cell designs reveals significant rate capability improvements in structured designs due to reduced diffusion and interfacial charge transfer polarization. A sensitivity analysis of geometric structure parameters shows further potential for performance improvement in terms of specific capacity and energy density. However, current constriction effects in the LLZO separator can deteriorate the rate capability. A more general perspective is then taken by analyzing the impact of changing SPE parameters. An energy density of 128 Wh kg⁻¹ at 1C, and 220 Wh kg⁻¹ at 1C with improved SPE parameters is achieved in the best case, approaching the target of 250 Wh kg⁻¹, which is currently achieved for conventional Li-ion batteries. Full article

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

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27 pages, 20905 KiB

Open AccessTutorial

Teaching Aid Regarding the Application of Advanced Organic Petrography in Recycling End-of-Life Lithium-Ion Batteries

by Bruno Valentim

Batteries 2024, 10(11), 391; https://doi.org/10.3390/batteries10110391 - 5 Nov 2024

Abstract

This teaching aid aims to illustrate a range of the most common materials in end-of-life (EoL) lithium-ion batteries (LIBs) to demonstrate the usefulness of advanced organic petrography in the characterization of EoL LIB materials and to assess the efficiency of LIB recycling processes [...] Read more.

This teaching aid aims to illustrate a range of the most common materials in end-of-life (EoL) lithium-ion batteries (LIBs) to demonstrate the usefulness of advanced organic petrography in the characterization of EoL LIB materials and to assess the efficiency of LIB recycling processes from the pre-processing stage up to the impurities of the metallurgical processes. Additionally, it may be useful for students, petrographers, and professionals in battery development and recycling. Full article

(This article belongs to the Section Battery Processing, Manufacturing and Recycling)

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16 pages, 3553 KiB

Open AccessFeature PaperArticle

Thermal Runaway Warning of Lithium Battery Based on Electronic Nose and Machine Learning Algorithms

by Zilong Pu, Miaomiao Yang, Mingzhi Jiao, Duan Zhao, Yu Huo and Zhi Wang

Batteries 2024, 10(11), 390; https://doi.org/10.3390/batteries10110390 - 5 Nov 2024

Abstract

Characteristic gas detection can be an efficient way to predict the degree of thermal runaway of a lithium battery. In this work, a sensor array consisting of three commercial MOS sensors was employed to discriminate between three target gases, CO, H₂ and [...] Read more.

Characteristic gas detection can be an efficient way to predict the degree of thermal runaway of a lithium battery. In this work, a sensor array consisting of three commercial MOS sensors was employed to discriminate between three target gases, CO, H₂ and a mixture of the two, which are characteristic gases released during the thermal runaway of lithium batteries. In this work, an integrated model that makes the classification stage results one of the feature inputs for the concentration regression stage was employed, successfully reducing the RMSE of the concentration regression results. In addition, we also explored the influence of the selection of the response time length on the classification and regression tasks, achieving the best results in a short time through the optimum algorithm. To assess the impact of time duration sensor data on the results, we selected four time windows of different length and extracted the corresponding sensor response data for subsequent processing. Initially, principal component analysis (PCA) was used to visualise the clustering of the three target gas samples at room temperature, providing a preliminary data analysis. For the classification phase, we chose three classification algorithms—MLP (Multilayer Perceptron), ELM (Extreme Learning Machine), and SVM (Support Vector Machine)—and performed a comprehensive comparison of their classification and generalisation abilities using grid search for hyperparameter optimisation and five-fold cross-validation. The results demonstrated that MLP achieved 99.23% classification accuracy during the 20 s response period. In the concentration regression phase, we combined the classification results with the raw features to create a new feature set, which was then input into a multi-output MLP regression model. The root mean square error (RMSE) employing the new feature set was used to measure the prediction error. Ultimately, the findings showed that the input of combined features significantly reduced the regression error for the mixed gas. Full article

(This article belongs to the Special Issue Advances in Lithium-Ion Battery Safety and Fire)

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