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Cycle Life Prediction of Battery-Supercapacitor Hybrids Using Artificial Neural Networks

机译:利用人工神经网络预测电池-超级电容器混合动力的循环寿命

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摘要

The cycle life of batteries and battery-supercapacitor hybrid systems was predicted using artificial neural networks. The presented techniques are able to predict the cycle life of a device based on a short (around 4% of the average cycle life) initial segment of the discharge curve. The prediction showed good performance with a correlation coefficient above 0.95. We were able to improve the predication further by considering readily available measurements of the device and usage.
机译:使用人工神经网络预测了电池和电池-超级电容器混合系统的循环寿命。所提出的技术能够基于放电曲线的短的初始段(平均循环寿命的约4%)来预测设备的循环寿命。预测显示出良好的性能,相关系数高于0.95。通过考虑随时可用的设备和使用情况的测量,我们能够进一步改善预测。

著录项

  • 来源
  • 会议地点 Vancouver(CA);Vancouver(CA)
  • 作者

    T. Weigert; Q. Tian; K. Lian;

  • 作者单位

    Department of Computer Science, Missouri University of Science and Technology,Rolla, MO 65401, USA;

    Department of Materials Science and Engineering, University of Toronto,Toronto, Ont. M5S 3E4, Canada;

    Department of Materials Science and Engineering, University of Toronto,Toronto, Ont. M5S 3E4, Canada;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 独立电源技术(直接发电);
  • 关键词

  • 入库时间 2022-08-26 14:19:39

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