期刊
ELECTROCHIMICA ACTA
卷 362, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.electacta.2020.137101
关键词
Lithium ion battery; State of health; Degradation mode; Diagnostic method
资金
- National Natural Science Foundation of China [51722105]
- Guangxi Key Research and Development Program of China
The whole life aging behavior and degradation mechanism of lithium ion battery (LIB) are critical to ensure the stability and reliability during practical operation. In this work, a new LIB aging modelling and diagnosing method is proposed based on open circuit voltage (OCV) analysis, through a two-stage segmented nonlinear regression algorithm to smooth incremental capacity (IC) curves for the reconstruction of universal OCV curves. Such algorithm can well reserve the chemical features of the IC curves, which enables the quantification of the loss of active materials and lithium inventory in a nondestructive manner with this OCV model-based diagnostic method. A case study of a commercial LiFePO4 (LFP) battery shows a satisfied accuracy of the model, realizing a quick identification of aging behavior and capacity degradation modes, as well as the parameter recognition of the battery internal resistance components. (C) 2020 Elsevier Ltd. All rights reserved.
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