Prediction of Remaining Useful Life of Lithium-ion Battery Based on Source-domain Battery Iterations Module and LSTM Neural Network

WANG Zipeng, HUANG Kai, SUN Kai, Li Senmao

PDF(26555 KB)
PDF(26555 KB)
Journal of Power Supply ›› 2025, Vol. 23 ›› Issue (7) : 294-303. DOI: 10.13234/j.issn.2095-2805.2025.7.294
Battery and Energy Storage

Prediction of Remaining Useful Life of Lithium-ion Battery Based on Source-domain Battery Iterations Module and LSTM Neural Network

    {{javascript:window.custom_author_en_index=0;}}
  • {{article.zuoZhe_EN}}
Author information +
History +

HeighLight

{{article.keyPoints_en}}

Abstract

{{article.zhaiyao_en}}

Key words

Cite this article

Download Citations
{{article.zuoZheEn_L}}. {{article.title_en}}. {{journal.qiKanMingCheng_EN}}. 2025, 23(7): 294-303 https://doi.org/10.13234/j.issn.2095-2805.2025.7.294

References

References

{{article.reference}}

Funding

RIGHTS & PERMISSIONS

{{article.copyrightStatement_en}}
{{article.copyrightLicense_en}}
PDF(26555 KB)

Accesses

Citation

Detail

Sections
Recommended

/