4.7 Article

Fractional-order modeling and SOC estimation of lithium-ion battery considering capacity loss

Journal

INTERNATIONAL JOURNAL OF ENERGY RESEARCH
Volume 43, Issue 1, Pages 417-429

Publisher

WILEY
DOI: 10.1002/er.4275

Keywords

capacity estimation; fractional-order model; lithium-ion battery; state-of-charge estimation

Funding

  1. Major Program of Chongqing Municipality [cstc2015zdcy-ztzx60006]
  2. Fundamental Research Funds for the Central Universities [106112016CDJXZ338825]
  3. National Key Research and Development Project [2018YFB0106102]
  4. National Natural Science Foundation of the People's Republic of China [51675062]

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For state-of-charge (SOC) estimation, the resistance deterioration and continuous capacity loss can lead to erroneous estimation results. In this paper, an SOC estimator of lithium-ion battery based on the fractional-order model and adaptive dual Kalman filtering algorithm is proposed first. Then, to improve the accuracy of SOC estimation considering capacity loss, the particle filter algorithm is applied to update capacity online in real time. Then, an SOC estimation method is proposed considering battery capacity loss. The simulation results show that the accuracy of battery capacity prediction based on particle filter is high under the condition of capacity loss.

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