Battery remaining useful life prediction at different discharge rates

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

22 Scopus Citations
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Original languageEnglish
Pages (from-to)212-219
Journal / PublicationMicroelectronics Reliability
Online published14 Sep 2017
Publication statusPublished - Nov 2017


Lithium-ion batteries are widely used in hybrid electric vehicles, consumer electronics, etc. As of today, given a room temperature, many battery prognostic methods working at a constant discharge rate have been proposed to predict battery remaining useful life (RUL). However, different discharge rates (DDRs) affect both usable battery capacity and battery degradation rate. Consequently, it is necessary to take DDRs into consideration when a battery prognostic method is designed. In this paper, we propose a discharge-rate-dependent battery prognostic method that is able to track usable battery capacity affected by DDRs in the process of battery degradation and to predict RUL at DDRs. An experiment was designed to collect accelerated battery life testing data at DDRs, which are used to investigate how DDRs influence usable battery capacity, to design a discharge-rate-dependent state space model and to validate the effectiveness of the proposed battery prognostic method. Results show that the proposed battery prognostic method can work at DDRs and achieve high RUL prediction accuracies at DDRs.

Research Area(s)

  • Different discharge rates, Lithium-ion batteries, Particle filter, Prognostics and health management, Remaining useful life