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A Comparative Study of Nano and Micro-Sized Silicon in Lithium-Ion Cells with a Nickel-Rich Cathode 富镍阴极锂离子电池中纳米级和微米级硅的比较研究
IF 3.9 4区 工程技术 Q2 ELECTROCHEMISTRY Pub Date : 2024-09-04 DOI: 10.1149/1945-7111/ad7297
Sheng S. Zhang
Reducing particle size has been widely adopted to mitigate the cracking and pulverization of silicon particles and to enhance electrode reaction kinetics for silicon electrodes in cycling. However, the increased surface area promotes parasitic reactions with electrolyte solvents. This work comparatively studies nano-sized silicon (Si-NP) and micro-sized silicon (Si-MP) as anodes in Li-ion cells using nickel-rich LiNi0.80Co0.1Mn0.1O2 (NCM811) as the cathode. The focus is on capacity, capacity retention, Coulombic efficiency (CE), and rate capability by changing the negative-to-positive capacity (N/P) ratio and charging cutoff voltage. It is found that Si-NP initially exhibits a CE above 90%, however, it rarely exceeds 98% in subsequent cycles, leading to rapid capacity fade. Additionally, increasing the N/P ratio and lowering the charging cutoff voltage does not obviously improve the cycling stability of Si-NP cells. Compared with Si-NP, Si-MP experiences lower capacity and lower CE in the initial several cycles. However, with continued cycling, both the capacity and CE gradually increase to a maximum and stably remain at ∼99.9%. The findings of this work suggest that, with its excellent rate capability, Si-MP may be more advantageous than Si-NP in developing practical Li-ion batteries, provided its low CE during initial cycles can be successfully addressed.
减小硅颗粒的尺寸已被广泛采用,以减轻硅颗粒的开裂和粉碎,并增强硅电极在循环过程中的电极反应动力学。然而,表面积的增加会促进与电解质溶剂的寄生反应。本研究比较性地研究了纳米级硅(Si-NP)和微米级硅(Si-MP)在锂离子电池中用作阳极的情况,阴极使用富镍 LiNi0.80Co0.1Mn0.1O2 (NCM811)。研究重点是通过改变负负容量比(N/P)和充电截止电压来研究容量、容量保持率、库仑效率(CE)和速率能力。研究发现,Si-NP 最初的 CE 超过 90%,但在随后的循环中很少超过 98%,从而导致容量快速衰减。此外,提高 N/P 比和降低充电截止电压并不能明显改善 Si-NP 电池的循环稳定性。与 Si-NP 相比,Si-MP 在最初的几个循环中容量较低,CE 也较低。然而,随着循环的持续进行,容量和 CE 都会逐渐增加到最大值,并稳定地保持在 ∼ 99.9%。这项工作的研究结果表明,Si-MP 具有优异的速率能力,在开发实用锂离子电池方面可能比 Si-NP 更具优势,但前提是能成功解决其在初始循环期间的低 CE 问题。
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引用次数: 0
Review—Machine Learning-Driven Advances in Electrochemical Sensing: A Horizon Scan 回顾--机器学习驱动的电化学传感技术进步:地平线扫描
IF 3.9 4区 工程技术 Q2 ELECTROCHEMISTRY Pub Date : 2024-09-03 DOI: 10.1149/1945-7111/ad6b4a
Kaviya Murugan, Karnan Gopalakrishnan, Kogularasu Sakthivel, Sakthinathan Subramanian, I-Cheng Li, Yen-Yi Lee, Te-Wei Chiu, Guo-Ping Chang-Chien
The burgeoning intersection of machine learning (ML) with electrochemical sensing heralds a transformative era in analytical science, pushing the boundaries of what’s possible in detecting and quantifying chemical substances with unprecedented precision and efficiency. This convergence has accelerated a number of discoveries, improving electrochemical sensors’ sensitivity, selectivity, and ability to comprehend complicated data streams in real-time. Such advancements are crucial across various applications, from monitoring health biomarkers to detecting environmental pollutants and ensuring industrial safety. Yet, this integration is not without its challenges; it necessitates navigating intricate ethical considerations around data use, ensuring robust data privacy measures, and developing specialized software tools that balance accessibility and security. As the field progresses, addressing these challenges head-on is essential for harnessing the full potential of ML-enhanced electrochemical sensing. This review briefly explores these dimensions, spotlighting the significant technological strides, the ethical landscape, and the dynamic interplay between open-source and proprietary software solutions while also casting a forward gaze at the promising future directions of this interdisciplinary venture.
机器学习(ML)与电化学传感的蓬勃发展预示着分析科学进入了一个变革性的时代,以前所未有的精度和效率推动了化学物质检测和量化的发展。这种融合加速了一系列发现,提高了电化学传感器的灵敏度、选择性和实时理解复杂数据流的能力。从监测健康生物标志物到检测环境污染物和确保工业安全,这些进步在各种应用中都至关重要。然而,这种整合并非没有挑战;它需要驾驭数据使用方面错综复杂的道德考量,确保强有力的数据隐私措施,以及开发兼顾可访问性和安全性的专业软件工具。随着该领域的不断进步,正面应对这些挑战对于充分发挥 ML 增强电化学传感的潜力至关重要。本综述简要探讨了这些方面的问题,重点介绍了重大的技术进步、伦理状况以及开源和专有软件解决方案之间的动态相互作用,同时还展望了这一跨学科事业充满希望的未来发展方向。
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引用次数: 0
Synergistic Approach of TiO2@MnZnO3 Heterostructure for Efficient Photoelectrochemical Water Splitting 利用 TiO2@MnZnO3 异质结构实现高效光电化学水分离的协同方法
IF 3.9 4区 工程技术 Q2 ELECTROCHEMISTRY Pub Date : 2024-09-03 DOI: 10.1149/1945-7111/ad728d
Fareeha Marriam, Aleena Arshad, Khadija Munawar, Muhammad Adil Mansoor, Mehdi Ebadi, Rabia Naeem
The superior kinetics of charge carriers and greater visible light absorption are important factors for enhancing photoelectrochemical performance. Herein, the core–shell heterostructure has been developed by encapsulating single-phase MnZnO3 over TiO2 nanotubes by aerosol-assisted chemical vapor deposition approach. The fabricated photoanodes have been characterized by employing various techniques including X-ray diffraction, Raman spectroscopy, scanning electron microscopy, energy dispersive X-ray spectroscopy, atomic force microscopy, and photoluminescence. Moreover, the mechanism for electron/hole transfer has been focused by a brief electrochemical investigation. The bilayer 1D/2D TiO2@MnZnO3 photoanode exhibited higher current density (2 mA cm−2) as compared to pristine TiO2-nanotubes (0.174 mA cm−2) at 1.52 V vs RHE. The superior photoactivity of heterostructure is attributed to the rapid transfer of photogenerated charge carriers via the Type-II mechanism. Furthermore, the reduced band gap (2.05 eV) accounts for good absorption in the visible region of light, while the interfacial electric field allowed the improved charge separation. The synergistic strategy in the present work demonstrates the promising significance of a heterojunction interface to optimize photovoltaic devices.
卓越的电荷载流子动力学和更强的可见光吸收能力是提高光电化学性能的重要因素。本文通过气溶胶辅助化学气相沉积方法,在 TiO2 纳米管上封装单相 MnZnO3,从而开发出核壳异质结构。利用 X 射线衍射、拉曼光谱、扫描电子显微镜、能量色散 X 射线光谱、原子力显微镜和光致发光等多种技术对制备的光阳极进行了表征。此外,还通过简短的电化学研究关注了电子/空穴传输机制。与原始 TiO2 纳米管(0.174 mA cm-2)相比,双层 1D/2D TiO2@MnZnO3 光阳极在 1.52 V 对比 RHE 时表现出更高的电流密度(2 mA cm-2)。异质结构优异的光活性归因于光生电荷载流子通过 II 型机制的快速转移。此外,降低的带隙(2.05 eV)使其在可见光区域具有良好的吸收性,而界面电场则改善了电荷分离。本研究中的协同策略表明,异质结界面对优化光伏设备具有重要意义。
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引用次数: 0
A Novel, Selective, and Fast Electrochemical Sensor Based on an 8-Nitroquinoline-Coated Pencil Graphite Electrode for Rutin Determination in Orange Juice 基于 8-硝基喹啉涂层铅笔石墨电极的新型、选择性、快速电化学传感器用于测定橙汁中的芦丁
IF 3.9 4区 工程技术 Q2 ELECTROCHEMISTRY Pub Date : 2024-09-03 DOI: 10.1149/1945-7111/ad7325
Farah En-Nakra, Demet Uzun, Erdoğan Hasdemir
In this study, we developed a facile and low-cost method to prepare a modified electrode by coating the pencil graphite electrode (PGE) surface with 8-nitroquinoline (8-NQ). The surface modification process was carried out by electrochemical reduction of 8-NQ on the PGE surface in ethanol solution. The optimum conditions were determined for the experimental studies. The differential pulse voltammetry was used to determine rutin with the modified electrode (8-NQ/PGE). The developed electrode showed excellent performance for rutin oxidation in a pH 3.0 Britton Robinson buffer (BR). In this media, linearly increasing anodic peak currents were observed with the concentration of rutin in two wide concentration ranges (i.e., 0.016–0.96 μM and 0.96‒19.73 μM), the sensor showed a low detection limit (i.e., 4.14 nM) (3 s m−1). It displayed good stability and selectivity. Also, it was used successfully for the determination of rutin in orange juice samples.
在这项研究中,我们开发了一种简便、低成本的方法,通过在铅笔石墨电极(PGE)表面涂覆 8-硝基喹啉(8-NQ)来制备改性电极。表面改性过程是在乙醇溶液中通过电化学还原 8-NQ 在铅笔石墨电极表面上进行的。实验研究确定了最佳条件。使用改性电极(8-NQ/PGE)进行微分脉冲伏安法测定芦丁。所开发的电极在 pH 值为 3.0 的布里顿罗宾逊缓冲液(BR)中显示出优异的芦丁氧化性能。在该介质中,随着芦丁浓度在两个较宽的浓度范围内(即 0.016-0.96 μM 和 0.96-19.73 μM)的增加,阳极峰电流呈线性增加,传感器显示出较低的检测限(即 4.14 nM)(3 s m-1)。它具有良好的稳定性和选择性。此外,它还成功地用于测定橙汁样品中的芦丁。
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引用次数: 0
Thermal Performance of a Cylindrical Li[Ni0.6Co0.2Mn0.2]O2/Graphite Battery based on the Electrochemical-Thermal Coupling Model 基于电化学-热耦合模型的圆柱形锂[Ni0.6Co0.2Mn0.2]O2/石墨电池的热性能
IF 3.9 4区 工程技术 Q2 ELECTROCHEMISTRY Pub Date : 2024-09-03 DOI: 10.1149/1945-7111/ad7290
Chao Zhang, Jin Shang, Yonglian Xiong, Ting Yi, Quanhui Hou, Xing Qian
The thermal safety of lithium-ion batteries has garnered significant attention due to its pivotal role in the field of new energy. In this work, a three-dimensional electrochemical-thermal coupling model based on the P2D model was established for predicting the thermal performance. The charge-discharge and temperature rise experiments via 18650 cylindrical Li[Ni0.6Co0.2Mn0.2]O2 / graphite batteries are designed to confirm the rationality of the model. The simulation results show that the highest temperature of the battery surface during discharging at 1 C and 4 C are 42.85 °C and 61.25 °C, and the experimental results are 42.50 °C and 62.85 °C, respectively. The electrode heat generation mainly comes from the reaction heat of cathode and anode during 1 C charge process, the maximum power is 1.2 W and 0.6 W, respectively. In the discharge process, the cathode dominates the reaction contribution of 1.02 W and the reaction heat power from the anode is only 0.016 W. The capacity of heat dissipation can be increased by enhancing the convective heat transfer coefficient and air velocity within a reasonable range. The proposed electrochemical-thermal coupling model is valuable to evaluate the heat behavior and promote the battery development.
由于锂离子电池在新能源领域发挥着举足轻重的作用,因此其热安全问题备受关注。本研究建立了基于 P2D 模型的三维电化学-热耦合模型,用于预测电池的热性能。设计了 18650 圆柱形锂[Ni0.6Co0.2Mn0.2]O2 / 石墨电池的充放电和温升实验,以证实模型的合理性。模拟结果表明,在 1 C 和 4 C 放电时,电池表面的最高温度分别为 42.85 ℃ 和 61.25 ℃,而实验结果分别为 42.50 ℃ 和 62.85 ℃。在 1 C 充电过程中,电极发热主要来自阴极和阳极的反应热,最大功率分别为 1.2 W 和 0.6 W。在放电过程中,阴极的反应热量占主导地位,为 1.02 W,而阳极的反应热量仅为 0.016 W。所提出的电化学-热耦合模型对评估热行为和促进电池开发具有重要价值。
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引用次数: 0
Thermal Battery Multi-Defects Detection and Discharge Performance Analysis Based on Computed Tomography Imaging 基于计算机断层扫描成像的热电池多缺陷检测和放电性能分析
IF 3.9 4区 工程技术 Q2 ELECTROCHEMISTRY Pub Date : 2024-09-02 DOI: 10.1149/1945-7111/ad728c
Dalong Tan, Hong Zhang, Zhaoguang Ma, Xia Zheng, Jing Liu, Fanyong Meng, Min Yang
To address the typical structural defects that are prone to occur during the preparation and storage processes of thermal battery, experiments of battery image acquisition were designed based on X-ray computed tomography system. An improved Yolov5s network was employed to achieve high-precision automatic detection of typical defects. Through the discharge experiment of thermal battery, discharge performance curves of normal batteries and three defective batteries were constructed. The impact and mechanisms of different defects on the discharge performance were analyzed based on the voltage curve. By designing an automatic stitching scheme, the phenomenon of interlayer information overlap caused by the increase of cone angle in digital radiography images was suppressed. To address the issues of low image contrast and limited defect data in thermal battery imaging, the defect dataset was expanded using the designed image preprocessing steps and improving the contrast of the images. For subtle defects that are difficult to identify, the introduced multi-head self-attention mechanism in Transformer and the use of Focal Loss instead of cross-entropy loss function were employed to improve the recognition accuracy of subtle defects while ensuring the detection speed. The comparative experiment shows that the improved network model has higher recognition accuracy compared to Faster R-CNN, SSD, Cascade R-CNN, EfficientDet and the original Yolov5s network. The recognition accuracy of typical defects in thermal batteries can reach 98.7%.
针对热电池在制备和储存过程中容易出现的典型结构缺陷,设计了基于 X 射线计算机断层扫描系统的电池图像采集实验。采用改进的 Yolov5s 网络实现了典型缺陷的高精度自动检测。通过热电池放电实验,构建了正常电池和三种缺陷电池的放电性能曲线。根据电压曲线分析了不同缺陷对放电性能的影响和机理。通过设计自动拼接方案,抑制了数字射线摄影图像因锥角增大而导致的层间信息重叠现象。针对热电池成像中图像对比度低和缺陷数据有限的问题,利用设计的图像预处理步骤扩大了缺陷数据集,提高了图像的对比度。针对难以识别的细微缺陷,在 Transformer 中引入了多头自注意机制,并使用 Focal Loss 代替交叉熵损失函数,在保证检测速度的同时提高了细微缺陷的识别精度。对比实验表明,与 Faster R-CNN、SSD、Cascade R-CNN、EfficientDet 和原始 Yolov5s 网络相比,改进后的网络模型具有更高的识别精度。对热电池典型缺陷的识别准确率可达 98.7%。
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引用次数: 0
Mechanism Analysis of the Reduction Process of the NiO-YSZ Anode of a Solid Oxide Fuel Cell by Hydrogen 固体氧化物燃料电池 NiO-YSZ 阳极氢还原过程的机理分析
IF 3.9 4区 工程技术 Q2 ELECTROCHEMISTRY Pub Date : 2024-09-02 DOI: 10.1149/1945-7111/ad6bc2
Xiaoyu Wang, Yongliang Zhang, Haiming Zhang, Wenwan Song, Tatsuya Kawada, Zewei Lyu, Minfang Han
Reduction of the nickel oxide-yttria stabilized zirconia (NiO-YSZ) anode is a significant step before the operation of a solid oxide fuel cell (SOFC). However, phenomena which occur during the reduction and their mechanism analyses are not summarized sufficiently. In this study, we investigated the influence of the hydrogen concentration, water vapor concentration of the reduction gas, Y2O3 content of the YSZ material of the anode, and temperature on the reduction process. The results showed that water vapor added to the hydrogen during reduction caused a temporary stasis period of the open circuit voltage. The length of the temporary stasis period was almost irrelevant to the water vapor concentration. During reduction, the length of the temporary stasis period of the open circuit voltage was negatively associated with hydrogen concentration and temperature, but positively associated with Y2O3 content of the YSZ material of the anode. After reduction, the SOFC showed better initial performance when the hydrogen concentration or the water vapor concentration during the reduction were higher. The classical shrinking core model can be used to explain these phenomena.
氧化镍-钇稳定氧化锆(NiO-YSZ)阳极的还原是固体氧化物燃料电池(SOFC)运行前的一个重要步骤。然而,在还原过程中发生的现象及其机理分析还没有得到充分总结。在本研究中,我们研究了氢气浓度、还原气体中的水蒸气浓度、阳极 YSZ 材料中的 Y2O3 含量和温度对还原过程的影响。结果表明,在还原过程中,氢气中加入的水蒸气会导致开路电压暂时停滞。暂时停滞期的长短几乎与水蒸气浓度无关。在还原过程中,开路电压暂时停滞期的长短与氢气浓度和温度呈负相关,但与阳极 YSZ 材料中的 Y2O3 含量呈正相关。还原后,当氢气浓度或还原过程中的水蒸气浓度较高时,SOFC 的初始性能较好。经典的缩芯模型可以用来解释这些现象。
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引用次数: 0
Reactive Condensation of Cr Vapor on Aluminosilicates Containing Alkaline Oxides 铬蒸气在含碱性氧化物的铝硅酸盐上的反应凝结
IF 3.9 4区 工程技术 Q2 ELECTROCHEMISTRY Pub Date : 2024-09-02 DOI: 10.1149/1945-7111/ad7061
T. K. van Leeuwen, A. Guerrero, R. Dowdy, B. Satritama, M. A. Rhamdhani, G. Will, P. Gannon
This study is part of a series with the objective of improving fundamental understanding of reactive condensation of Chromium (Cr) vapors, which are generated from Cr containing alloys used in many high-temperature (>500 °C) process environments and can form potentially problematic condensed hexavalent (Cr(VI)) species downstream. This study specifically focuses on the effects of alkaline oxide additives in aluminosilicate fibers on Cr condensation and speciation. Cr vapors were generated by flowing high-temperature (800 °C) air containing 3% water vapor over chromia (Cr2O3) powder, with aluminosilicate fiber samples positioned downstream where the temperature decreases (<500 °C). Total condensed Cr and ratios of oxidation states were measured using inductively coupled plasma optical emission spectroscopy (ICP-OES) and diphenyl carbazide (DPC) colorimetric/direct UV–vis spectrophotometric analyses. Results indicate presence of hexavalent Cr (Cr(VI)) species condensed on all samples investigated. The ratio of Cr(VI) to total Cr detected was consistently higher on aluminosilicate fiber samples containing alkaline oxide (CaO and MgO) additions. Computational thermodynamic equilibrium modelling corroborated experimental results showing stabilities of Ca and Mg chromate (Cr(VI)) compounds. Comparative results and analyses are presented and discussed to help inform mechanistic understanding and future related research and engineering efforts.
本研究是系列研究的一部分,旨在加深对铬(Cr)蒸气反应性冷凝的基本了解。铬(Cr)蒸气是从许多高温(500 °C)工艺环境中使用的含铬合金中产生的,并可能在下游形成有潜在问题的冷凝六价(Cr(VI))物质。本研究特别关注铝硅酸盐纤维中的碱性氧化物添加剂对铬冷凝和标示的影响。铬(Cr2O3)粉末上流动着含有 3% 水蒸汽的高温(800 °C)空气,产生铬蒸气,铝硅酸盐纤维样品位于温度降低的下游(<500 °C)。使用电感耦合等离子体光发射光谱(ICP-OES)和二苯基卡巴肼(DPC)比色/直接紫外-可见分光光度分析法测量了凝聚铬总量和氧化态比率。结果表明,在所有调查样品中都凝结有六价铬(Cr(VI))。在添加了碱性氧化物(CaO 和 MgO)的硅酸铝纤维样品上,检测到的六价铬与总铬之比一直较高。计算热力学平衡模型证实了实验结果,显示了铬酸钙和铬酸镁(Cr(VI))化合物的稳定性。本文介绍并讨论了比较结果和分析,以帮助人们了解机理,并为今后的相关研究和工程工作提供信息。
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引用次数: 0
Redox Activity Modulation in Extended Fluorenone-Based Flow Battery Electrolytes with π-π Stacking Effect 具有π-π堆积效应的扩展芴酮基液流电池电解质中的氧化还原活性调制
IF 3.9 4区 工程技术 Q2 ELECTROCHEMISTRY Pub Date : 2024-09-02 DOI: 10.1149/1945-7111/ad7324
Ruozhu Feng, Xueyun Zheng, Peter S. Rice, J. David Bazak, Aaron Hollas, Yuyan Shao, Yangang Liang, Wei Wang
Redox flow battery shows promise for grid-scale energy storage. Aqueous organic redox flow batteries are particularly popular due to their potentially low material cost and safe water-based electrolyte. Commonly, redox active molecules used in this field feature aromatic rings, and increasing π-aromatic conjugation has been a popular strategy to achieve high energy density, high power density, and reduced crossover in new material design. However, this approach can inadvertently hinder redox activity depending on redox mechanism. This study reveals the underlying π-π stacking effect in extended aromatic redox active compounds, where aromatic radical intermediates are involved in the redox process. We report a molecular design strategy to mitigate the negative effect of π-π stacking by altering solvation dynamics and introducing molecular steric hindrance.
氧化还原液流电池有望用于电网规模的能源储存。水性有机氧化还原液流电池因其潜在的低材料成本和安全的水基电解质而特别受欢迎。该领域使用的氧化还原活性分子通常具有芳香环,而增加π-芳香共轭一直是新材料设计中实现高能量密度、高功率密度和减少交叉的流行策略。然而,根据氧化还原机制的不同,这种方法可能会无意中阻碍氧化还原活性。本研究揭示了扩展芳香氧化还原活性化合物中潜在的 π-π 堆叠效应,其中芳香自由基中间体参与了氧化还原过程。我们报告了一种分子设计策略,通过改变溶解动力学和引入分子立体阻碍来减轻 π-π 堆积的负面影响。
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引用次数: 0
Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Simplified Electrochemical Model and TSO-TCN 基于简化电化学模型和 TSO-TCN 的锂离子电池剩余使用寿命预测
IF 3.9 4区 工程技术 Q2 ELECTROCHEMISTRY Pub Date : 2024-09-02 DOI: 10.1149/1945-7111/ad728f
Chen Lin, Dongjiang Yang, Zhongkai Zhou
Accurate prediction of the remaining useful life (RUL) of lithium-ion battery is critical in practical applications, but is challenging due to the presence of multiple aging pathways and nonlinear degradation mechanisms. In this paper, a method for RUL prediction is proposed combined with battery capacity aging mechanism based on transient search optimization (TSO)-temporal convolutional network (TCN) algorithm. First, the particle swarm optimization algorithm is used to derive three health indicators directly related to capacity loss from a simplified electrochemical model. Then, the TCN parameters are optimized with transient search algorithm to obtain the optimal prediction model. Finally, the RUL prediction are compared with other typical algorithms, and the results show that the proposed method can accurately predict the RUL of lithium-ion battery, and the life prediction error is within 10 cycles. Compared to TCN, the prediction results remain accurate even with less training data, and the error metrics are reduced by about 50% with the maximum error only 7 cycles from the 250th charge/discharge cycle.
准确预测锂离子电池的剩余使用寿命(RUL)在实际应用中至关重要,但由于存在多种老化途径和非线性降解机制,因此具有挑战性。本文基于瞬态搜索优化(TSO)-时态卷积网络(TCN)算法,提出了一种结合电池容量老化机制的 RUL 预测方法。首先,使用粒子群优化算法从简化的电化学模型中推导出与容量损失直接相关的三个健康指标。然后,使用瞬态搜索算法优化 TCN 参数,以获得最佳预测模型。最后,将 RUL 预测结果与其他典型算法进行比较,结果表明所提出的方法能准确预测锂离子电池的 RUL,且寿命预测误差在 10 个循环以内。与 TCN 相比,即使训练数据较少,预测结果仍然准确,误差指标减少了约 50%,最大误差仅为第 250 次充放电循环的 7 个循环。
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引用次数: 0
期刊
Journal of The Electrochemical Society
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