Battery remaining useful life prediction at different discharge rates. (November 2017)

• Record Type: Journal Article
• Authors: Wang, Dong; Yang, Fangfang; Zhao, Yang; Tsui, Kwok-Leung
• Is Part Of: Microelectronics and reliability. Volume 78(2017)
• Page Start: 212
• Page End: 219
• Publication Date: 2017-11
• Subjects: Remaining useful life -- Lithium-ion batteries -- Particle filter -- Prognostics and health management -- Different discharge rates; Electronic apparatus and appliances -- Reliability -- Periodicals; Miniature electronic equipment -- Periodicals; Appareils électroniques -- Fiabilité -- Périodiques; Équipement électronique miniaturisé -- Périodiques; Electronic apparatus and appliances -- Reliability; Miniature electronic equipment; Periodicals; 621.3815
• DOI: 10.1016/j.microrel.2017.09.009
• Languages: English
• ISSNs: 0026-2714

Abstract

Abstract: 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. Graphical abstract: (a)–(c) Design of an experiment for collection of lithium-ion battery degradation data at different discharge rates; (d) a sequence of different discharge rates; (e) degradation data corresponding to the sequence of different discharge rates; (f) battery remaining useful life prediction at different discharge rates. Highlights: An experiment for battery capacity degradation at different discharge rates is designed. The influence of different discharge rates on usable capacity is investigated. A more general empirical battery degradation model is proposed. A discharge-rate-dependent battery prognostic method is proposed. Battery remaining useful life at different discharge rates is predicted.