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Degradation Predictions of Lithium Iron Phosphate Battery

Authors :
Yuya Hato
Yasuhiro Daisho
Shoichi Inami
Yushi Kamiya
Chien Hung Chen
Toshio Hirota
Source :
World Electric Vehicle Journal, Volume 7, Issue 1, Pages 25-31
Publication Year :
2015
Publisher :
Multidisciplinary Digital Publishing Institute, 2015.

Abstract

Degradation mechanisms of lithium iron phosphate battery have been analyzed with calendar tests and cycle tests. To quantify capacity loss with the life prediction equation, it is seen from the aspect of separating the total capacity loss into calendar capacity and real cycle capacity loss. The real cycle capacity loss of total capacity loss was derived by subtracting the calendar capacity loss parts during cycle tests. It is considered that calendar capacity loss is dominated by SEI formation. On the other hand, real cycle capacity loss includes structure disorder of electrodes and promotion of SEI growth such as delamination and regrowth. Generally, the test results indicated that capacity loss increases under high temperature and SOC condition, and SOC range (ΔSOC) is not related to the loss. However, we founded that the test results under 5℃ condition do not exactly show the same tendency of degradation. As a result, the life prediction equation is based on the chemical kinetics and it can only be adopted only beyond the 15℃ temperature limitation. At this time in life prediction equation, to take ΔSOC into consideration and describe the real cycle capacity loss specifically with amounts of lithium-ion intercalation/deintercalation, the processing amount of current is adopted as the standard of capacity degradation instead of the cycle number. Finally, it is considered to be possible that certain reactions such as further structure disorder or lithium plating caused under low temperature. However, we also founded that DC internal resistance tests results indicated that only calendar capacity loss can apply to chemical kinetics. It is necessary to consider the other construction method of the life prediction equation in the future

Details

Language :
English
ISSN :
20326653
Database :
OpenAIRE
Journal :
World Electric Vehicle Journal
Accession number :
edsair.doi.dedup.....7c478472b6cc3ea6425197fede025646
Full Text :
https://doi.org/10.3390/wevj7010025