Author
Listed:
- Tiansi Wang
(School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China)
- Hao Wang
(School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China)
- Xiaoling Shen
(School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China)
- Chenhao Lu
(School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China)
- Lei Pei
(Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China)
- Yixiang Xu
(School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China)
- Wanlin Wang
(Farasis Energy, Zhenjiang 212013, China)
- Huanhuan Li
(Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China)
Abstract
As an important component of current power and energy storage systems, lithium-ion batteries have essential scientific significance and application value in terms of accurately and reliably diagnosing their aging to determine system performance, identify potential faults in modules, and prolong their service life. For this purpose, this paper first briefly describes the working principle of lithium-ion batteries and illustrates the possible impacts of various aging mechanisms on the state of battery capacity. Secondly, starting from both implementable and laboratory perspectives, it sorts out and summarizes the diagnostic mechanisms and applicable scenarios of current typical battery aging state assessment and diagnosis methods. Then, targeting the specific aging mechanisms involved in batteries, it elaborates on the targeted diagnosis processes for each aging mechanism. Finally, combined with implementable and laboratory diagnosis methods, it systematically summarizes a highly standardized and universal routine diagnosis process for battery aging. In addition, in combination with the latest development of aging diagnosis and related technologies, this paper reflects on and discusses the possible future development directions of battery diagnosis technologies.
Suggested Citation
Tiansi Wang & Hao Wang & Xiaoling Shen & Chenhao Lu & Lei Pei & Yixiang Xu & Wanlin Wang & Huanhuan Li, 2025.
"Review of Aging Mechanism and Diagnostic Methods for Lithium-Ion Batteries,"
Energies, MDPI, vol. 18(14), pages 1-35, July.
Handle:
RePEc:gam:jeners:v:18:y:2025:i:14:p:3884-:d:1706469
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