Article, 2024

High-precision collaborative estimation of lithium-ion battery state of health and remaining useful life based on call activation function library-long short term memory neural network algorithm

JOURNAL OF ENERGY STORAGE, ISSN 2352-152X, Volume 83, 10.1016/j.est.2024.110749

Contributors

Wang, Yangtao [1] Wang, Shunli 0000-0001-6019-778X (Corresponding author) [1] [2] Fan, Yongcun [1] Xie, Yanxin [1] Hao, Xueyi [1] Guerrero, Josep M. [3]

Affiliations

  1. [1] Southwest Univ Sci & Technol, Sch Informat Engn, Mianyang 621010, Peoples R China
    2. [NORA names: China; Asia, East];
  2. [2] Sichuan Univ, Coll Elect Engn, Chengdu 610065, Peoples R China
    3. [NORA names: China; Asia, East];
  3. [3] Aalborg Univ, Dept Energy & Technol, Aalborg, Denmark
    4. [NORA names: AAU Aalborg University; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

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Keywords

Call activation function library, Health factor, Lithium-ion battery, Prognostics and health management system, Remaining useful life

Data Provider: Clarivate

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