Calendar aging of commercial graphite/LiFePO4 cell - Predicting capacity fade under time dependent storage conditions

被引:216
作者
Grolleau, Sebastien [1 ,2 ]
Delaille, Arnaud [1 ]
Gualous, Hamid [2 ]
Gyan, Philippe [3 ]
Revel, Renaud [4 ]
Bernard, Julien [4 ]
Redondo-Iglesias, Eduardo [5 ]
Peter, Jeremy [5 ]
机构
[1] CEA LITEN DTS, Lab Elect Storage CEA LSE, D-73377 Le Bourget Du Lac, France
[2] LUSAC ESIX Normandie, F-50130 Octeville, France
[3] TCR LAB 012, DREAM DELTA 68580, F-78288 Guyancourt, France
[4] IFP Energies Nouvelles, Etab Lyon, F-69360 Solaize, France
[5] IFSTTAR LTE, F-69675 Bron, France
关键词
Li-ion battery aging; C/LiFePO4; Storage; Capacity fade experimental data; Capacity fade model; Time varying environment; LITHIUM-ION BATTERIES; SOLID-ELECTROLYTE INTERPHASE; CYCLE-LIFE; MECHANISMS; MODEL; DEGRADATION; SIMULATION; PROGRAM;
D O I
10.1016/j.jpowsour.2013.11.098
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070305 [高分子化学与物理];
摘要
In applications such as electrical transportation, most of the battery life is spent under storage. Understanding and estimating aging under storage, also named as calendar aging, is therefore a prerequisite for cell life prediction. This work investigates aging behavior upon storage of a commercial 15 Ah lithium-ion graphite/iron phosphate cell. Performance decline during 450 days of storage under nine stationary conditions is analyzed using non-destructive electrochemical tests. Temperature is found to be more detrimental than State of Charge (SoC). Most often, degradation models express the accumulated degradation with respect to time and aging conditions. In this article, a simple modeling approach is proposed focusing on the degradation rate to predict capacity fade. This permits predicting cell degradation under time dependent storage conditions (SoC and temperature) which are usually experienced in real applications. Model prediction is compared to experimental calendar aging data obtained over 625 days in a controlled time dependent temperature storage conditions. Predictions are in good agreement with experimental results as the absolute error on capacity prediction never exceeds 3% over 400 days and 5% over 625 days. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:450 / 458
页数:9
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