Journal
INFORMATION SCIENCES
Volume 259, Issue -, Pages 359-368Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2013.06.038
Keywords
Lithium iron phosphate battery; Pattern recognition; Life cycle test; Reliability diagnosis; Cluster analysis; Failure analysis
Categories
Funding
- National Basic Research Program of China (973) [2009CB220107]
Ask authors/readers for more resources
In this paper, we present experimental data on the resistance, capacity, and life cycle of lithium iron phosphate batteries collected by conducting full life cycle testing on one type of lithium iron phosphate battery, and we analyse that data using the data mining method of pattern recognition. We also predict battery reliability using cluster analysis. A strategy for enhancing the reliability of lithium iron phosphate batteries is proposed based on a statistical analysis and study of the macromechanism of product failures. We show in practice that the average life cycle of a battery is increased by 45.5% after adopting a new strategy that we suggest. The strategy is effective for mass-producing reliable lithium iron phosphate batteries and instructive for improving the industry of lithium iron phosphate battery production, as well as the quality of its products. (C) 2013 Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available