An improved model for remaining useful life prediction on capacity degradation and regeneration of lithium-ion battery

Abstract

The regeneration phenomena of the lithium-ion battery arewidely existed in reality but rarely studied due to the gapbetween experiment conditions and practical working conditions.In this paper, the capacity regeneration phenomena areconsidered during the degradation process of batteries. Animproved empirical model incorporating both rest time anddischarge cycles for remaining useful life (RUL) prediction isproposed. The degradation process and regeneration processhave been described by different components and integratedto formulate the whole model. The dual estimation frameworkis employed to decouple the states and parameters duringthe degradation and regeneration process. The datasetsfrom NASA Prognostics Center of Excellence (PCoE) havebeen adopted for model validation. The proposed model iscompared with other empirical model and also different estimationmethods. The results are satisfactory, and demonstratethe capability of the proposed model for the RUL predictionof Lithium-ion battery.