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  <front>
    <journal-meta>
      <journal-title-group><journal-title>SET Proceedings</journal-title></journal-title-group>
      <issn pub-type="epub">2978-4387</issn>
      <publisher><publisher-name>Caravel Press</publisher-name></publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.65582/set.2017.189</article-id>
      <article-id pub-id-type="publisher-id">2017.189</article-id>
      <title-group><article-title>High Precision State-of-Charge (SOC) Estimation of Lithium-ion Batteries Based on Adaptive Model of Noise Suppression</article-title></title-group>
    <contrib-group>
      <contrib contrib-type="author">
        <name><surname>Wu</surname><given-names>Tiezhou</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <email>WTZ315@163.com</email>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>Xiang</surname><given-names>Fuchao</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <email>543206584@qq.com</email>
      </contrib>
      <contrib contrib-type="author">
        <name><surname>Hao</surname><given-names>Shan</given-names></name>
        <xref ref-type="aff" rid="aff1"/>
        <email>1348980399@qq.com</email>
      </contrib>
      <aff id="aff1">Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy, Hubei University of Technology , Wuhan China</aff>
    </contrib-group>
      <pub-date publication-format="electronic" date-type="pub"><day>13</day><month>07</month><year>2017</year></pub-date>
      <volume>16</volume>
      <isbn publication-format="electronic">9791220022033</isbn>
      <fpage>1</fpage>
      <lpage>10</lpage>
      <self-uri xlink:href="https://caravelpress.com/proceedings/set/papers/2017.189"/>
      <history>
        <date date-type="received"><string-date>13 July 2017</string-date></date>
      </history>
      <permissions>
        <copyright-statement>© 2017 Copyright WSSET</copyright-statement>
        <copyright-year>2017</copyright-year>
      </permissions>
      <abstract><p>In estimation of state-of-charge (SOC) for lithium batteries, the accuracy of the noise initial value will affect the SOC estimation accuracy. Based on the multi-iterative extended Kalman filter algorithm (IEKF), the second-order resistor-capacitor (RC) model with high precision and moderate amount of calculation is selected as the lithium-ion battery model. The SOC estimation is further improved by the noise suppression in the battery model. Experiments show that the SOC estimation error is reduced by 2% compared with the no noise suppression, and the adaptive noise suppression of the battery equivalent model is achieved by using the IEKF algorithm with high estimation accuracy for the lithium-ion battery SOC estimation system.</p></abstract>
      <kwd-group kwd-group-type="author">
        <kwd>SOC estimation</kwd>
        <kwd>IEKF algorithm</kwd>
        <kwd>noise suppression</kwd>
        <kwd>second order RC model</kwd>
      </kwd-group>
      <conference>
        <conf-date>17 to 20 July 2017</conf-date>
        <conf-name>16th International Conference on Sustainable Energy Technologies</conf-name>
        <conf-acronym>SET2017</conf-acronym>
        <conf-num>16</conf-num>
        <conf-loc>Bologna, Italy</conf-loc>
      </conference>
    </article-meta>
  </front>
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