open access publication

Article, 2023

Health prognostics for lithium-ion batteries: mechanisms, methods, and prospects

Energy & Environmental Science, ISSN 1754-5706, 1754-5692, Volume 16, 2, Pages 338-371, 10.1039/d2ee03019e

Contributors

Che, Yunhong 0000-0002-7350-0001 [1] Hu, Xiaosong [2] Lin, Xianke 0000-0001-5695-248X [3] Guo, Jia 0000-0002-3882-9266 [1] Teodorescu, Remus 0000-0002-2617-7168 [1]

Affiliations

  1. [1] Aalborg University
  2. [NORA names: AAU Aalborg University; University; Denmark; Europe, EU; Nordic; OECD];
  3. [2] Chongqing University
  4. [NORA names: China; Asia, East];
  5. [3] University of Ontario Institute of Technology
  6. [NORA names: Canada; America, North; OECD]

Abstract

Critical review of main aging mechanisms and health prognostic methods for lithium-ion batteries. Comprehensive summary of challenges and prospects for future trends with potential solutions. Lithium-ion battery aging mechanism analysis and health prognostics are of great significance for a smart battery management system to ensure safe and optimal use of the battery system. This paper provides a comprehensive review of aging mechanisms and the state-of-the-art health prognostic methods and summarizes the main challenges and research prospects for battery health prognostics. First, the complex relationships among aging mechanisms, aging modes, influencing factors, and aging types are reviewed and summarized. Then, the battery health prognostic methods are divided according to different time scales and objectives, which include the short-term state of health estimation, long-term end-of-life prediction, and degradation trajectory prediction, followed by a detailed review of each prognostic task and method. For consistency, we first provide a clear and concise description of each method, showing the similarities and peculiarities of these methods, and then review several representative works. After that, comparative evaluations are conducted. The main advantages and disadvantages of each prognostic task and prognostic method are analyzed in detail. Next, key challenges are presented by considering the specific characteristics of each prognostic task. Moreover, for each challenge, potential solutions are presented and discussed. These proposed potential solutions to the main challenges are beneficial and can be considered by researchers in their further studies. Finally, the future trends of battery health prognostics are discussed, and several new ideas for battery health prognostics are proposed.

Keywords

age, aging mechanism analysis, aging mechanisms, aging modes, aging type, analysis, battery, battery health prognostics, battery management system, battery system, challenges, characteristics, comparative evaluation, complex relationship, comprehensive review, comprehensive summary, consistency, critical review, degradation, description, disadvantages, end-of-life prediction, estimation, evaluation, factors, health, health estimation, health prognostics, influencing factors, lithium-ion, lithium-ion batteries, management system, mechanical analysis, mechanism, method, mode, objective, optimal use, peculiarities, potential solutions, prediction, prognostic method, prognostic tasks, prognostication, prospects, relationship, representative works, research, research prospects, review, scale, short-term state, significance, similarity, smart battery management system, solution, state of health estimation, state-of-the-art, study, summary, system, task, time, time scales, trajectory prediction, trends, type, use, work

Funders

  • National Natural Science Foundation of China
  • Ministry of Science and Technology of the People's Republic of China
  • The Velux Foundations

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