利用数量有限的电压-容量曲线,基于阻抗谱进行电池退化评估

IF 15 1区 工程技术 Q1 ENERGY & FUELS
Yue Sun , Rui Xiong , Xiangfeng Meng , Xuanrou Deng , Hailong Li , Fengchun Sun
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引用次数: 0

摘要

降解预测对于确保电池安全可靠地运行至关重要。然而,仅仅依靠容量来描述老化特性并不能全面反映电池的健康状况。本研究利用深度学习方法,探索了使用有限数量的部分电压-容量曲线来评估电池退化的潜力,该方法可用于车载应用。本文提出了一个序列到序列模型,用于预测电池降解过程中的电化学阻抗谱。该模型只使用特定电压范围内的容量序列,以固定的电压增量从有限的循环次数开始,可以端到端的方式灵活地适应不同的生命阶段。根据开发的退化数据集,对所提出的方法进行了验证。阻抗谱预测的均方根误差小于 1.48 mΩ。与电化学过程相关的电容和电阻可从获得的阻抗谱中进一步提取,从而促进对电池降解的全面评估。由于所需的测量数据数量有限,所提出的方法可以降低数据存储要求和计算需求,从而实现快速、全面的老化诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Battery degradation evaluation based on impedance spectra using a limited number of voltage-capacity curves

Degradation prediction is crucial for ensuring safe and reliable operation of batteries. However, relying solely on capacity to characterize aging cannot comprehensively represent the health status of the battery. This work explores the potential of using a limited number of partial voltage-capacity curves to evaluate battery degradation with the aid of deep learning approaches, which can be used for onboard applications. A sequence-to-sequence model is proposed to predict the electrochemical impedance spectra during battery degradation. It only uses capacity sequences within a specific voltage range at fixed voltage increments from a limited number of cycles, which can be flexibly adapted to different life stages in an end-to-end manner. The proposed method has been validated based on the developed degradation dataset. The root mean square errors for the prediction of impedance spectra are less than 1.48 mΩ. Capacities and resistances associated with electrochemical processes can be further extracted from the obtained impedance spectra, facilitating a comprehensive evaluation of battery degradation. As a limited number of measured data are needed, the proposed method can reduce data storage requirements and computational demands, which enables fast and comprehensive aging diagnosis.

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来源期刊
Etransportation
Etransportation Engineering-Automotive Engineering
CiteScore
19.80
自引率
12.60%
发文量
57
审稿时长
39 days
期刊介绍: eTransportation is a scholarly journal that aims to advance knowledge in the field of electric transportation. It focuses on all modes of transportation that utilize electricity as their primary source of energy, including electric vehicles, trains, ships, and aircraft. The journal covers all stages of research, development, and testing of new technologies, systems, and devices related to electrical transportation. The journal welcomes the use of simulation and analysis tools at the system, transport, or device level. Its primary emphasis is on the study of the electrical and electronic aspects of transportation systems. However, it also considers research on mechanical parts or subsystems of vehicles if there is a clear interaction with electrical or electronic equipment. Please note that this journal excludes other aspects such as sociological, political, regulatory, or environmental factors from its scope.
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