Study on Remaining Useful Life Prediction of Lithium-ion Batteries Based on Charge Transfer Resistance

doi:10.3901/JME.2021.14.105

Abstract

Abstract: Prediction of remaining useful life facilitates the efficient and appropriate management and assessment for lithium-ion batteries. Electrochemical impedance can reflect properties of physical and chemical processes inside a lithium-ion battery. It is widely used in studies of battery life issues. Especially, the charge transfer resistance describes the difficulty of the reaction at the interphase of the electrodes. It can be applied to characterize the aging state. Through the experiments under four aging conditions, the evolution of the charge transfer resistance with the aging process is obtained. Several empirical aging models are evaluated with the Bayesian information criterion. And a first-order polynomial aging model is chosen and established. On this basis, a remaining useful life prediction method based on the particle filter algorithm is proposed. The results show that the remaining useful life of the lithium-ion batteries can be accurately predicted with the method, thus providing the necessary battery life information for the battery management and assessment.

Key words: lithium-ion batteries, impedance, charge transfer resistance, particle filter algorithm, remaining useful life

CLC Number:

TM912

WANG Xueyuan, LI Rikang, WEI Xuezhe, DAI Haifeng, ZHENG Yuejiu. Study on Remaining Useful Life Prediction of Lithium-ion Batteries Based on Charge Transfer Resistance[J]. Journal of Mechanical Engineering, 2021, 57(14): 105-117.

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