Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Wiener Processes with Considering the Relaxation Effect

Xiaodong Xu, Chuanqiang Yu, Shengjin Tang, Xiaoyan Sun, Xiaosheng Si and Lifeng Wu
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Xiaodong Xu: High-Tech Institute of Xi’an, Xi’an 710025, China
Chuanqiang Yu: High-Tech Institute of Xi’an, Xi’an 710025, China
Shengjin Tang: High-Tech Institute of Xi’an, Xi’an 710025, China
Xiaoyan Sun: High-Tech Institute of Xi’an, Xi’an 710025, China
Xiaosheng Si: High-Tech Institute of Xi’an, Xi’an 710025, China
Lifeng Wu: College of Information Engineering, Capital Normal University, Beijing 100048, China

Energies, 2019, vol. 12, issue 9, 1-17

Abstract: Remaining useful life (RUL) prediction has great importance in prognostics and health management (PHM). Relaxation effect refers to the capacity regeneration phenomenon of lithium-ion batteries during a long rest time, which can lead to a regenerated useful time (RUT). This paper mainly studies the influence of the relaxation effect on the degradation law of lithium-ion batteries, and proposes a novel RUL prediction method based on Wiener processes. This method can simplify the modeling complexity by using the RUT to model the recovery process. First, the life cycle of a lithium-ion battery is divided into the degradation processes that eliminate the relaxation effect and the recovery processes caused by relaxation effect. Next, the degradation model, after eliminating the relaxation effect, is established based on linear Wiener processes, and the model for RUT is established by using normal distribution. Then, the prior parameters estimation method based on maximum likelihood estimation and online updating method under the Bayesian framework are proposed. Finally, the experiments are carried out according to the degradation data of lithium-ion batteries published by NASA. The results show that the method proposed in this paper can effectively improve the accuracy of RUL prediction and has a strong engineering application value.

Keywords: lithium-ion battery; relaxation; remaining useful life; regenerated useful time; Wiener processes; Bayesian framework; maximum likelihood estimation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

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