Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (2): 307-313.doi: 10.23940/ijpe.20.02.p13.307313

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Lithium-ion Battery Performance Degradation Recognition Method based on SOC Estimation

Jin Taoa, Hao Gangab*()   

  1. aSchool of Engineering, Naval University of Engineering, Wuhan, 430033, China
    bSchool of Mechanical and Electrical Automation, Wuhan City Vocational College, Wuhan, 430064, China
  • Submitted on ; Revised on ; Accepted on
  • Contact: Hao Gang
  • About author:

    Jin Tao obtained a Bachelor's degree in Engineering in Marine Engineering from the Naval University of Engineering and a Doctorate in Structural Mechanics from Huazhong University of Science and Technology. His research direction is ship safety science and technology.

    Hao Gang obtained a Bachelor's degree in Mechanical Engineering from Huazhong Agricultural University, a Master's degree in Marine Engineering from Huazhong University of Science and Technology, and a Ph.D. from the Naval University of Engineering. His research interests are ship safety science and technology.


The development of ship electric propulsion technology poses new challenges for ship energy storage, ship intelligence and electrification. The green new energy application represented by lithium batteries will drive the technological innovation of green ships and smart ships. Lithium-ion batteries have a residual capacity attenuation during cyclic charging and discharging, and the identification of performance degradation has important implications for the operation and maintenance of lithium-ion batteries. In this paper, the SOC estimation value of real-time data collected by the lithium-ion battery cycle charging and discharging is adopted. After denoising by the outlier algorithm, the FCM algorithm is used to establish the performance degradation model. Finally, the change of the membership function value of the normal cluster center is used as the lithium ion battery. Performance degradation assessment results, showing that the method can effectively and intuitively evaluate the performance degradation of lithium-ion batteries.

Key words: Li ion battery, Cycle life SOC estimation, Performance degradation