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Analysis of performance degradation and residual life prediction of batteries for electric vehicles under driving conditions
Author(s) -
Li Wenhua,
Jiao Zhipeng,
Zhou Lulu
Publication year - 2019
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22831
Subject(s) - battery (electricity) , residual , degradation (telecommunications) , automotive engineering , electric vehicle , lithium (medication) , lithium iron phosphate , state of charge , test data , engineering , computer science , reliability engineering , simulation , electrical engineering , algorithm , medicine , power (physics) , physics , quantum mechanics , endocrinology , software engineering
The analysis of residual life prediction of batteries for electric vehicles under driving conditions was performed based on the degradation data. This article, characteristics of lithium iron phosphate battery performance degradation as the object, mainly considers two factors about the charge–discharge rate and vibration stress, first, the lithium battery performance degradation test simulating a car in a real driving environment is designed, which provides the lithium battery performance test reference. Then, the model parameters were obtained based on the test data. Finally, the performance degradation model and residual life prediction model of the lithium battery based on the Wiener process are established. This method not only has a high prediction accuracy, but also avoids the construction of a complex battery mechanism degradation model. What is more, this article provides a good perspective for residual life prediction in simplified experiments saving cost. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.