Battery Full Life Cycle Management and Health Prognosis Based on Cloud Service and Broad Learning
Dear editor, This letter presents battery full life cycle management and health prognosis based on cloud service and broad learning. Specifically, a cloud-based framework for battery full life cycle management is presented. Then, the broad learning method is proposed for battery state-of-health (SOH...
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Veröffentlicht in: | IEEE/CAA journal of automatica sinica 2022-08, Vol.9 (8), p.1540-1542 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Dear editor, This letter presents battery full life cycle management and health prognosis based on cloud service and broad learning. Specifically, a cloud-based framework for battery full life cycle management is presented. Then, the broad learning method is proposed for battery state-of-health (SOH) prediction. The features of charging data including the constant current time, constant voltage time, and the total charging time are selected as the input characteristics of the network to estimate SOH. Moreover, the empirical mode decomposition is carried out on the initial data to restore the most essential attenuation trajectory of battery capacity. Experimental results show that the proposed method can provide more accurate battery SOH prediction than several state-of-the-art methods. |
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ISSN: | 2329-9266 2329-9274 |
DOI: | 10.1109/JAS.2022.105779 |