Leveraging Structures in Fault Diagnosis for Lithium-Ion Battery Packs

被引:0
作者
Farakhor, Amir [1 ]
Wu, Di [2 ]
Wang, Yebin [3 ]
Fang, Huazhen [1 ]
机构
[1] Univ Kansas, Dept Mech Engn, Lawrence, KS 66045 USA
[2] Pacific Northwest Natl Lab, Richland, WA 99352 USA
[3] Mitsubishi Elect Res Labs, Cambridge, MA 02139 USA
来源
2024 IEEE 7TH INTERNATIONAL CONFERENCE ON INDUSTRIAL CYBER-PHYSICAL SYSTEMS, ICPS 2024 | 2024年
关键词
battery systems; fault diagnosis; moving horizon estimation;
D O I
10.1109/ICPS59941.2024.10640051
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Lithium-ion battery packs consist of a varying number of single cells, designed to meet specific application requirements for output voltage and capacity. Effective fault diagnosis in these battery packs is an essential prerequisite for ensuring their safe and reliable operation. To address this need, we introduce a novel model-based fault diagnosis approach. Our approach distinguishes itself by leveraging informative structural properties inherent in battery packs such as uniformity among the constituent cells, and sparsity of fault occurrences to enhance its fault diagnosis capabilities. The proposed approach formulates a moving horizon estimation (MHE) problem, incorporating such structural information to estimate different fault signals-specifically, internal short circuits, external short circuits, and voltage and current sensors faults. We conduct various simulations to evaluate the performance of the proposed approach under different fault types and magnitudes. The obtained results validate the proposed approach and promise effective fault diagnosis for battery packs.
引用
收藏
页数:6
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