扩散
电池(电)
锂(药物)
降级(电信)
离子
粒子(生态学)
材料科学
荷电状态
健康状况
锂离子电池
断层(地质)
计算机科学
控制理论(社会学)
汽车工程
化学
电气工程
工程类
热力学
物理
控制(管理)
人工智能
功率(物理)
地质学
内分泌学
医学
海洋学
地震学
有机化学
作者
Pengya Fang,Anhao Zhang,Xiaoxiao Sui,Di Wang,Liping Yin,Zhenhua Wen
出处
期刊:ACS omega
[American Chemical Society]
日期:2023-08-30
卷期号:8 (36): 32884-32891
被引量:11
标识
DOI:10.1021/acsomega.3c04222
摘要
The analysis of performance degradation in lithium-ion batteries plays a crucial role in achieving accurate and efficient fault diagnosis as well as safety management. This paper proposes a method for studying the degradation pattern of lithium-ion batteries and establishing the structure-activity relationship between internal and external parameters by employing a lumped particle diffusion model. To simulate real-world operating conditions, a cycle life test was conducted with the constant current-constant voltage (CC-CV) charge mode and the discharge mode under New European Driving Cycle (NEDC) working condition. The test aimed to analyze the variations in the external macroscopic characteristic parameters of the battery. Building upon this analysis, a lumped particle diffusion model was constructed, and the model parameters were identified using the Levenberg-Marquardt (L-M) algorithm. Subsequently, the ohmic, activation, and concentration losses of the battery under different aging conditions were determined, revealing the internal state evolution during the degradation process of lithium-ion batteries. The findings indicate that the lumped particle diffusion model provides a comprehensive explanation of the internal mechanisms contributing to the performance degradation of lithium-ion batteries. Moreover, the proposed method offers a novel perspective for the real-time quantitative analysis of lithium-ion battery performance degradation.
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