State-of-Health Prognosis for Lithium-Ion Batteries Considering the Limitations in Measurements via Maximal Information Entropy and Collective Sparse Variational Gaussian Process

Prognostics and health management (PHM) for electronic devices is intricate yet crucial in an era of electricity. The impending future of electric vehicles and clean energy requires more in-depth scrutiny and monitoring of their storage elements, lithium-ion batteries. State-of-health (SOH), as one...

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Veröffentlicht in:	IEEE access 2020, Vol.8, p.188199-188217
Hauptverfasser:	Xiang, Ming, He, Yigang, Zhang, Hui, Zhang, Chaolong, Wang, Lei, Wang, Chenyuan, Sui, Chunsong
Format:	Artikel
Sprache:	eng
Schlagworte:	Clean energy Data points Degradation Diagnostic systems Electric vehicles Electronic devices Entropy (Information theory) Feature extraction Gaussian process Integrated circuit modeling Interpolation k-nearest neighbors Lithium Lithium-ion batteries Mathematical model maximal information entropy (MIE) Missing data Prognosis Prognostics and health management prognostics and health management (PHM) Rechargeable batteries sparse variational Gaussian process state-of-health Statistical analysis Statistical methods Storage batteries
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