Modeling the effect of fast charge on the cycle life of a lithium-ion battery and comparison with experimental data

Alternative Title
Koo Yookyung
Author(s)
구유경
Alternative Author(s)
Koo Yookyung
Advisor
신치범
Department
일반대학원 에너지시스템학과
Publisher
The Graduate School, Ajou University
Publication Year
2020-02
Language
eng
Alternative Abstract
The fast charge for battery electric vehicle (BEV) is a possible route to reduce range anxiety and increase the utility. The fast charge is, however, reported to have negative effects on battery cycle life and performance. This thesis aims to develop modeling methodology of a lithium-ion battery (LIB) considering the effects of fast charge on cycle life for BEV applications. This thesis includes mathematical modeling for prediction battery cycle life, performance, and electrical/thermal behavior of LIBs and searching for the optimal fast charge protocol to improve cycle life of LIBs. To search for the optimal fast charge protocol, fast charge protocols are compared each other on factors affected cycle life such as temperature raise, temperature imbalance, and the imbalance of state of charge. To account for the aging effects of the LIB cell due to fast charge procedures, the key modeling parameters are expressed as a function of the square root of a novel modeling variable named as the accumulated thermal burden. The cycling tests are performed under the five different charge scenarios. The performance degradation of the aged LIB cell is different depending on charge techniques during cycling test. In order to validate the modeling methodology introduced in this thesis, the modeling results towards the changes of the discharge curves and two-dimensional temperature distributions of the aged LIB cell under five different charge scenarios are compared with the experimental measurements. The electrical and thermal behaviors predicted by the modeling for the aged LIB cell such as capacity fade, cell voltage drop under load, and peak temperature rise show good agreement with the experimental data.
URI
https://dspace.ajou.ac.kr/handle/2018.oak/21122
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Graduate School of Ajou University > Department of Energy Systems > 4. Theses(Ph.D)
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