A hybrid data driven framework considering feature extraction for battery state of health estimation and remaining useful life predictionOA
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
School of Artificial Intelligence,Anhui University,Hefei 230009,ChinaState Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun 130022,ChinaSchool of Electrical Engineering and Automation,Wuhan University,Wuhan 430000,ChinaSchool of Information Engineering,Southwest University of Science and Technology,Mianyang 621010,ChinaSchool of Pharmacy and Life Sciences,Robert Gordon University,Aberdeen,AB10-7GJ,UK
State of heathImproved sparrow search algorithmRemaining useful lifeVariational mode decompositionMulti-kernel support vector regressionFeature extraction
State of heathImproved sparrow search algorithmRemaining useful lifeVariational mode decompositionMulti-kernel support vector regressionFeature extraction
《新能源与智能载运（英文）》 2025 (1)
51-60,10
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).
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