Batteries

Batteries are the heart and the bottleneck of portable electronic systems. They power electronics and determine the system run time, with the size and volume determining factors in their design and implementation. Understanding the material properties of the battery components—anode, cathode, electrolyte, and separator—and their interaction is necessary to establish selection criteria based on their correlations with the battery metrics: capacity, current density, and cycle life. This review studies material used in the four battery components from the perspective and the impact of seven ions (Li+, Na+, K+, Zn2+, Ca2+, Mg2+, and Al3+), employed in commercial and research batteries. In addition, critical factors of sustainability of the supply chains—geographical raw materials origins vs. battery manufacturing companies and material properties (Young’s modulus vs. electric conductivity)—are mapped. These are key aspects toward identifying the supply chain vulnerabilities and gaps for batteries. In addition, two battery applications, smartphones and electric vehicles, in light of challenges in the current research, commercial fronts, and technical prospects, are discussed. Bringing the next generation of batteries necessitates a transition from advances in material to addressing the technical challenges, which the review has powered.

Wendy Pantoja

Jaime Andres Perez-Taborda

Alba Avila

Tug-of-War in the Selection of Materials for Battery Technologies

电池技术材料选择中的拉锯战

The mechanical pressure that arises from the external structure of the automotive lithium battery module and its fixed devices can give rise to the concentration and damage of the internal stress inside the battery and increase the risks of battery degradation and failure. Commercial batteries cannot be disassembled, and the diffusion stress distribution at different times during discharge is notoriously difficult to determine. This paper, therefore, establishes the electrochemical force-coupling model based on the electrochemical and diffusion mechanics principles of batteries and studies the internal stress distribution of the battery under the diffusion stress of the electrode-material level and external pressure. Mainly driven by the electrochemical potential of the electrode particle diffusion stress stemming from the lithium-concentration difference inside and outside the particles, rupture is more likely to occur at the surface of the negative-electrode active particle at the end of discharge or the beginning of charging, as shown in simulation analysis. The variation in the volume of electrode material also leads to different stress and strain inside different areas, with the order of strain and stress being negative active material &gt; negative collector fluid &gt; positive active material &gt; positive fluid. Therefore, huge stress and deformation will first cause the negative active particles to deviate from the fluid gradually and squeeze the diaphragm, resulting in mechanical failure accordingly.

Wei Shi

Ruofan Xu

Changjiang Han

Bingxiang Sun

Jin Chai

Jiachang Liu

Xuewen Jiao

Jiale Xiong

Yinghao Li

Stress Analysis of Electrochemical and Force-Coupling Model for Ternary Lithium-Ion Batteries

三元锂离子电池的电化学与力耦合模型应力分析

This paper presents a comprehensive review of the thermal management strategies employed in cylindrical lithium-ion battery packs, with a focus on enhancing performance, safety, and lifespan. Effective thermal management is critical to retain battery cycle life and mitigate safety issues such as thermal runaway. This review covers four major thermal management techniques: air cooling, liquid cooling, phase-change materials (PCM), and hybrid methods. Air-cooling strategies are analyzed for their simplicity and cost-effectiveness, while liquid-cooling systems are explored for their superior heat dissipation capabilities. Phase-change materials, with their latent heat absorption and release properties, are evaluated as potential passive cooling solutions. Additionally, hybrid methods, such as combining two or more strategies, are discussed for their synergistic effects in achieving optimal thermal management. Each strategy is assessed in terms of its thermal performance, energy efficiency, cost implications, and applicability to cylindrical lithium-ion battery packs. The paper provides valuable insights into the strengths and limitations of each technique, offering a comprehensive guide for researchers, engineers, and policymakers in the field of energy storage. The findings contribute to the ongoing efforts to develop efficient and sustainable thermal management solutions for cylindrical lithium-ion battery packs in various applications.

Mohammad Ahmadian-Elmi

Peng Zhao

Review of Thermal Management Strategies for Cylindrical Lithium-Ion Battery Packs

圆柱形锂离子电池组热管理策略综述

The investigation of electric vehicle technologies has increased significantly in the last few years. These vehicles can substantially reduce the environmental impact of the transportation sector. In electric cars, the battery is a crucial element. The batteries are made up of several stacked cells to meet the requirements of the propulsion system. Battery equalizer circuits take active measures to ensure that a particular variable is kept inside an allowable range in all cells. Inductor-based equalizers are very popular since the equalization current is controlled. This paper proposes a single-inductor architecture with a reduced number of components. The proposed topology can transfer energy from adjacent cell-to-cell or adjacent string-to-string. This paper analyzes the operation of the converter, its design, and the design of the controller. Furthermore, a comparison of the proposed equalizer with other inductor-based schemes was made considering the component count, stress on devices, equalization time, driver complexity, and other parameters. The theoretical efficiency of the proposed equalizer obtained was 84.9%, which is competitive with other literature solutions. The impact of battery size on the number of circuit components was also analyzed. Finally, simulation results in open load and changes of current through the battery conditions were performed to validate the theoretical analysis.

Alfredo Alvarez-Diazcomas

Juvenal Rodríguez-Reséndiz

Roberto V. Carrillo-Serrano

An Improved Battery Equalizer with Reduced Number of Components Applied to Electric Vehicles

应用于电动汽车的减少元件数量的改进型电池均衡器

Nb2CTx is an important member of MXene family. It has attracted widespread attention because of its abundant functional groups, high hydrophilicity, high electrical conductivity as well as low ion transport barrier, showing great potential in various applications. In order to utilize the advantages of Nb2CTx MXene, the progress of preparation, properties and applications are reviewed in this work. This work focuses on different methods of Nb2CTx preparation and applications in electrochemical energy storage (supercapacitors and secondary batteries), electrocatalytic hydrogen evolution, photocatalytic hydrogen evolution, sensors, etc. Additionally, the main problems of self-stacking and prospect of Nb2CTx MXene are discussed.

Guozhen Guan

Fengmei Guo

A Review of Nb2CTx MXene: Synthesis, Properties and Applications

Nb2CTx MXene的综述：合成、性质与应用

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.

Rafael Martínez-Sánchez

Angel Molina-García

Antonio Mateo-Aroca

Alfonso P. Ramallo-González

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

评估基于非侵入式和无监督原型的镍氢（NiMH）电池再生专利

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.

Martino Airoldi

Ullrich Steiner

Ilja Gunkel

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

纳米结构固态聚合物电解质阻抗中的界面效应作用

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.

Yuchao Wu

Balakumar Balasingam

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

基于电化学阻抗谱的电池等效电路模型参数提取方法比较

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.

Sahar Qaadan

Aiman Alshare

Alexander Popp

Benedikt Schmuelling

Prediction of Lithium-Ion Battery Health Using GRU-BPP

使用GRU-BPP预测锂离子电池健康状况

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.

Juncheng Fu

Zhengxiang Song

Jinhao Meng

Chunling Wu

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

基于改进黑翼风筝算法优化的深度混合核极限学习机预测锂离子电池健康状态

短名
Journal Impact	4.55
国际分区	MATERIALS SCIENCE, MULTIDISCIPLINARY(Q2)
期刊索引	SCI Q2中科院 4 区

ISSN	2313-0105
h-index	44
国内分区	化学(4区)化学电化学(3区)化学能源与燃料(4区)化学材料科学综合(4区)

涉及主题	物理量子力学工程类化学材料科学热力学功率（物理）有机化学物理化学电池（电）计算机科学电极生物电气工程复合材料冶金医学电化学心理学电解质内科学化学工程内分泌学精神科锂（药物）数学纳米技术无机化学地质学
出版信息	出版商: Multidisciplinary Digital Publishing Institute (MDPI)，出版周期: ，期刊类型: journal，开源期刊: 是
基本数据	创刊年份: 2015，原创研究文献占比: 85.86%，自引率:N.A.， Gold OA占比: 0.00%
期刊费用	$详情
平均审稿周期	网友分享经验：7 Weeks

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