Similarity Based Remaining Useful Life Prediction for Lithium-ion Battery under Small Sample Situation Based on Data Augmentation

Wang, Zongyao; Shangguan, Wei; Peng, Cong; Cai, Baigen

doi:10.17531/ein/175585

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Tytuł artykułu

Similarity Based Remaining Useful Life Prediction for Lithium-ion Battery under Small Sample Situation Based on Data Augmentation

Autorzy

Wang Zongyao , Shangguan Wei , Peng Cong , Cai Baigen

Treść / Zawartość

Pełne teksty:

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Identyfikatory

DOI

10.17531/ein/175585

Warianty tytułu

Języki publikacji

Abstrakty

Lithium-ion batteries find extensive application in transportation, energy storage, and various other fields. However, gathering a significant volume of degradation data for the same type of lithium-ion battery devices becomes challenging in practice due to variations in battery operating conditions and electrochemical properties, among other factors. In this small sample situation, accurately predicting the remaining useful life (RUL) of the battery holds great significance. This paper presents a RUL prediction method that is based on data augmentation and similarity measures. Firstly, by utilizing the single exponential model and Sobol sampling techniques, it is possible to generate realistic degradation trajectories, even with just one complete run-to-failure degradation dataset. Subsequently, the similarity between the generated prediction reference trajectories and actual degradation trajectories is evaluated using the Pearson distance. Following that, the point estimation of RUL is performed through weighted averaging. Then, the uncertainty of the RUL predictions is quantified using kernel density estimation. Finally, the effectiveness of the proposed RUL prediction method is validated using two NASA lithium-ion battery datasets. Results demonstrate the practicality and effectiveness of the proposed method.

Słowa kluczowe

lithium-ion batteries remaining useful life similarity-based prediction Sobol sampling kernel density estimation

Wydawca

Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne

Czasopismo

Eksploatacja i Niezawodność

Rocznik

2024

Tom

Vol. 26, no. 1

Strony

art. no. 175585

Opis fizyczny

Bibliogr. 49 poz., rys., tab., wykr.

Twórcy

autor

Wang Zongyao

22110059@bjtu.edu.cn

School of Electronics and Information Engineering, Beijing jiaotong university, Beijing, 100044, China

https://orcid.org/0000-0002-4153-627X

autor

Shangguan Wei

wshg@bjtu.edu.cn

School of Electronics and Information Engineering, Beijing jiaotong university, Beijing, 100044, China
ChinaState Key Laboratory of Rail Traffic control and safety, Beijing jiaotong university, Beijing, 100044, China

autor

Peng Cong

19111064@bjtu.edu.cn

School of Electronics and Information Engineering, Beijing jiaotong university, Beijing, 100044, China

autor

Cai Baigen

bgcai@bjtu.edu.cn

School of Electronics and Information Engineering, Beijing jiaotong university, Beijing, 100044, China
ChinaState Key Laboratory of Rail Traffic control and safety, Beijing jiaotong university, Beijing, 100044, China

Bibliografia

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