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An easy-to-parameterise physics-informed battery model and its application towards lithium-ion battery cell design, diagnosis, and degradation

机译:一种易于参数化的物理信息电池模型及其在锂离子电池设计,诊断和退化中的应用

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摘要

Accurate diagnosis of lithium ion battery state-of-health (SOH) is of significant value for many applications, to improve performance, extend life and increase safety. However, in-situ or in-operando diagnosis of SOH often requires robust models. There are many models available however these often require expensive-to-measure ex situ parameters and/or contain unmeasurable parameters that were fitted/assumed. In this work, we have developed a new empirically parameterised physics-informed equivalent circuit model. Its modular construction and low-cost parametrisation requirements allow end users to parameterise cells quickly and easily. The model is accurate to 19.6 mV for dynamic loads without any global fitting/optimisation, only that of the individual elements. The consequences of various degradation mechanisms are simulated, and the impact of a degraded cell on pack performance is explored, validated by comparison with experiment. Results show that an aged cell in a parallel pack does not have a noticeable effect on the available capacity of other cells in the pack. The model shows that cells perform better when electrodes are more porous towards the separator and have a uniform particle size distribution, validated by comparison with published data. The model is provided with this publication for readers to use.
机译:锂离子电池健康状态(SOH)的准确诊断对于许多应用而言具有重要价值,对于提高性能,延长使用寿命和提高安全性具有重要意义。但是,SOH的原位或操作中诊断通常需要可靠的模型。有许多可用的模型,但是这些模型通常需要昂贵的测量异地参数和/或包含已拟合/假定的无法测量的参数。在这项工作中,我们开发了一个新的根据经验参数化的物理信息等效电路模型。其模块化的结构和低成本的参数化要求使最终用户可以快速,轻松地对单元进行参数设置。对于动态负载,该模型精确到19.6 mV,而无需任何全局拟合/优化,仅单个元素即可。模拟了各种降解机制的后果,并探索了降解电池对电池组性能的影响,并与实验进行了比较。结果表明,平行电池组中的老化电池对电池组中其他电池的可用容量没有明显影响。该模型表明,当电极朝向隔板更多孔且具有均匀的粒径分布时,电池的性能会更好,已与公开数据进行了比较。该出版物随附该模型,以供读者使用。

著录项

  • 来源
    《Journal of power sources》 |2018年第30期|66-79|共14页
  • 作者单位

    Imperial Coll London, Dept Mech Engn, Exhibit Rd,South Kensington Campus, London SW7 2AZ, England;

    Imperial Coll London, Dyson Sch Design Engn, London SW7 2AZ, England;

    Imperial Coll London, Dept Earth Sci & Engn, London SW7 2AZ, England;

    Imperial Coll London, Dept Mech Engn, Exhibit Rd,South Kensington Campus, London SW7 2AZ, England;

    Imperial Coll London, Dept Mech Engn, Exhibit Rd,South Kensington Campus, London SW7 2AZ, England;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Lithium ion battery; Modelling; Empirical; Parameterisation; Physics model; Degradation;

    机译:锂离子电池建模经验参数化物理模型退化;
  • 入库时间 2022-08-18 00:21:26

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