State of health battery estimator enabling degradation diagnosis: Model and algorithm description

被引:118
作者
Dubarry, Matthieu [1 ]
Berecibar, M. [2 ,3 ]
Devie, A. [1 ]
Ansean, D. [4 ]
Omar, N. [2 ]
Villarreal, I. [3 ]
机构
[1] Univ Hawaii Manoa, SOEST, Hawaii Nat Energy Inst, 1680 East West Rd,POST 109, Honolulu, HI 96822 USA
[2] Vrije Univ Brussel, MOBI Res Grp, Pl Laan 2, B-1050 Elsene, Belgium
[3] IK4 Ikerian, Arizmendiarrieta 2, Arrasate Mondragon 20500, Spain
[4] Univ Oviedo, Polytech Sch Engn, Dept Elect Engn, Battery Res Lab, Gijon 33204, Asturias, Spain
关键词
Li-ion; SOH; BMS; LFP; LTO; Incremental capacity; LITHIUM-ION BATTERIES; INCREMENTAL CAPACITY ANALYSIS; HIGH-POWER; OF-HEALTH; MANAGEMENT-SYSTEMS; PATH DEPENDENCE; VOLTAGE CURVES; ONLINE STATE; CELL; PACKS;
D O I
10.1016/j.jpowsour.2017.05.121
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
This paper presents a novel approach for automated state of health estimation that offers similar advantages to the adaptive methods without being computation intensive. The onboard diagnosis uses a look-up table compiling the evolution of selected features of interest under any possible degradation paths. The look-up table is built from simulations of the impact of degradation on the cell electro-chemical behavior. This multi-step method only requires intensive calculations prior to deployment. This approach is validated by experimental data from cells that underwent normal aging as well as plating and overcharge. Additional validation via modeling showed that the method is able to diagnose cells undergoing any degradation scenario automatically in close to 90% of cases. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:59 / 69
页数:11
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