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A hybrid data driven framework considering feature extraction for battery state of health estimation and remaining useful life prediction

Yuan Chen Wenxian Duan Yigang He Shunli Wang Carlos Fernandez

新能源与智能载运（英文）2025，Vol.3Issue(1)：51-60,10.

新能源与智能载运（英文）2025，Vol.3Issue(1)：51-60,10.DOI:10.1016/j.geits.2024.100160

A hybrid data driven framework considering feature extraction for battery state of health estimation and remaining useful life prediction

Yuan Chen ¹Wenxian Duan ²Yigang He ³Shunli Wang ⁴Carlos Fernandez⁵

作者信息

1. School of Artificial Intelligence,Anhui University,Hefei 230009,China
2. State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun 130022,China
3. School of Electrical Engineering and Automation,Wuhan University,Wuhan 430000,China
4. School of Information Engineering,Southwest University of Science and Technology,Mianyang 621010,China
5. School of Pharmacy and Life Sciences,Robert Gordon University,Aberdeen,AB10-7GJ,UK
折叠

摘要

关键词

State of heath/Improved sparrow search algorithm/Remaining useful life/Variational mode decomposition/Multi-kernel support vector regression/Feature extraction

Key words

State of heath/Improved sparrow search algorithm/Remaining useful life/Variational mode decomposition/Multi-kernel support vector regression/Feature extraction

引用本文复制引用

Yuan Chen,Wenxian Duan,Yigang He,Shunli Wang,Carlos Fernandez..A hybrid data driven framework considering feature extraction for battery state of health estimation and remaining useful life prediction[J].新能源与智能载运（英文）,2025,3(1):51-60,10.

基金项目

This work was supported by the National Natural Science Foundation of China(Grant number 51577046),the State Key Program of the Na-tional Natural Science Foundation of China(Grant number 51637004),and the National Key Research and Development Plan"Important Sci-entific Instruments and Equipment Development"(Grant number 2016YFF0102200). （Grant number 51577046）

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