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Battery parameter identification with Pseudo Random Binary Sequence excitation (PRBS)

机译:伪随机二进制序列激励(PRBS)的电池参数识别

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摘要

This paper extends previous work on the use of maximum length sequences as tools for parameter estimation within electrochemical batteries. An improved technique using a simplified monopolar current pulse excitation strategy allows identification of Randies' model equivalent circuit values, which can be subsequently employed in state-of-charge and state-of-health algorithms. Within the approach the problems associated with establishing bulk capacitance over a short time period are avoided. Instead, using readily identifiable parameters (surface capacitance, series resistance and charge transfer resistance) comparison of parameters for new and aged batteries is carried out, and a potential indicator for State of Health described. Experimental results are presented to verify the proposed technique.
机译:本文扩展了以前使用最大长度序列作为电化学电池参数估计工具的工作。使用简化的单极性电流脉冲激励策略的改进技术可以识别Randies模型的等效电路值,随后可以将其用于充电状态和健康状态算法。在该方法内,避免了与在短时间内建立大容量电容相关的问题。取而代之的是,使用易于识别的参数(表面电容,串联电阻和电荷转移电阻)对新旧电池的参数进行比较,并描述了健康状况的潜在指标。实验结果被提出来验证所提出的技术。

著录项

  • 来源
    《Journal of power sources》 |2011年第22期|p.9398-9406|共9页
  • 作者单位

    Vxl Power Ltd. Station Road. North Hykeham. Lincoln. LN6 3Q_Y. UK;

    Department of Electrical and Electronic Engineering. The University of Sheffield, UK;

    Department of Electrical and Electronic Engineering. The University of Sheffield, UK;

  • 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

    batteries; modelling; prbs; state estimation;

    机译:电池;造型;prbs;状态估计;
  • 入库时间 2022-08-18 00:24:36

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