TY - JOUR
T1 - The Degradation Behavior of LiFePO4/C Batteries during Long-Term Calendar Aging
AU - Sui, Xin
AU - Maciej, Swierczynski
AU - Teodorescu, Remus
AU - Stroe, Daniel-Ioan
PY - 2021/3/20
Y1 - 2021/3/20
N2 - With widespread applications for lithium-ion batteries in energy storage systems, the performance degradation of the battery attracts more and more attention. Understanding the battery’s long-term aging characteristics is essential for the extension of the service lifetime of the battery and the safe operation of the system. In this paper, lithium iron phosphate (LiFePO4) batteries were subjected to long-term (i.e., 27–43 months) calendar aging under consideration of three stress factors (i.e., time, temperature and state-of-charge (SOC) level) impact. By means of capacity measurements and resistance calculation, the battery’s long-term degradation behaviors were tracked over time. Battery aging models were established by a simple but accurate two-step nonlinear regression approach. Based on the established model, the effect of the aging temperature and SOC level on the long-term capacity fade and internal resistance increase of the battery is analyzed. Furthermore, the storage life of the battery with respect to different stress factors is predicted. The analysis results can hopefully provide suggestions for optimizing the storage condition, thereby prolonging the lifetime of batteries.
AB - With widespread applications for lithium-ion batteries in energy storage systems, the performance degradation of the battery attracts more and more attention. Understanding the battery’s long-term aging characteristics is essential for the extension of the service lifetime of the battery and the safe operation of the system. In this paper, lithium iron phosphate (LiFePO4) batteries were subjected to long-term (i.e., 27–43 months) calendar aging under consideration of three stress factors (i.e., time, temperature and state-of-charge (SOC) level) impact. By means of capacity measurements and resistance calculation, the battery’s long-term degradation behaviors were tracked over time. Battery aging models were established by a simple but accurate two-step nonlinear regression approach. Based on the established model, the effect of the aging temperature and SOC level on the long-term capacity fade and internal resistance increase of the battery is analyzed. Furthermore, the storage life of the battery with respect to different stress factors is predicted. The analysis results can hopefully provide suggestions for optimizing the storage condition, thereby prolonging the lifetime of batteries.
KW - Lithium-ion battery
KW - Long-term calendar aging
KW - Capacity fade
KW - Internal resistance increase
KW - Lifetime modelling
KW - Nonlinear regression
UR - http://www.scopus.com/inward/record.url?scp=85106408197&partnerID=8YFLogxK
U2 - 10.3390/en14061732
DO - 10.3390/en14061732
M3 - Journal article
VL - 14
JO - Energies
JF - Energies
SN - 1996-1073
IS - 6
M1 - 1732
ER -