Prediction of Remaining Useful Life Based on SSA-RVM-PF Method for Lithium-ion Battery

Meng Zhou, Jing Wang, Chang Cai,Chang Wang

2022 5th International Symposium on Autonomous Systems (ISAS)（2022）

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Abstract

To improve the prediction accuracy of the remaining useful life of lithium-ion battery, a novel SSA-RVM-PF prediction method is proposed. The key prediction mechanism of the proposed method is based on the relevance vector machine (RVM) method. Based on the strong regression ability of RVM, the optimal degradation trajectory of battery capacity can be predicted. Meanwhile, a sparrow search algorit...

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Key words

Degradation,Lithium-ion batteries,Support vector machines,Simulation,Prediction methods,Relevance vector machines,Prediction algorithms

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