Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM

Joint Authors

Zhang, Chaolong
Yuan, Lifeng
Xiang, Sheng
Wang, Jinping
He, Yigang

Source

Computational Intelligence and Neuroscience

Issue

Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2015-08-30

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Biology

Abstract EN

Lithium-ion batteries are widely used in many electronic systems.

Therefore, it is significantly important to estimate the lithium-ion battery’s remaining useful life (RUL), yet very difficult.

One important reason is that the measured battery capacity data are often subject to the different levels of noise pollution.

In this paper, a novel battery capacity prognostics approach is presented to estimate the RUL of lithium-ion batteries.

Wavelet denoising is performed with different thresholds in order to weaken the strong noise and remove the weak noise.

Relevance vector machine (RVM) improved by differential evolution (DE) algorithm is utilized to estimate the battery RUL based on the denoised data.

An experiment including battery 5 capacity prognostics case and battery 18 capacity prognostics case is conducted and validated that the proposed approach can predict the trend of battery capacity trajectory closely and estimate the battery RUL accurately.

American Psychological Association (APA)

Zhang, Chaolong& He, Yigang& Yuan, Lifeng& Xiang, Sheng& Wang, Jinping. 2015. Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1057781

Modern Language Association (MLA)

Zhang, Chaolong…[et al.]. Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1057781

American Medical Association (AMA)

Zhang, Chaolong& He, Yigang& Yuan, Lifeng& Xiang, Sheng& Wang, Jinping. Prognostics of Lithium-Ion Batteries Based on Wavelet Denoising and DE-RVM. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1057781

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1057781