A lead-acid battery's remaining useful life prediction by using electrochemical model in the Particle Filtering framework

• Published in: Energy (Oxford) Vol. 120; pp. 975 - 984
• Main Authors: Lyu, Chao, Lai, Qingzhi, Ge, Tengfei, Yu, Honghai, Wang, Lixin, Ma, Na
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.02.2017; Elsevier BV
• Subjects: Batteries; Computer simulation; Effectiveness; Electrochemical modeling; Electrochemistry; equations; Filters; Filtration; Lead acid batteries; Life prediction; Mathematical models; Measurement; Parameter identification; Particle Filter framework; prediction; Remaining useful life prediction; Simulation; State variable; Remaining useful life prediction; Effectiveness; Electrochemical modeling; Particle Filter framework

Accurate prediction of battery's remaining useful life (RUL) is significant for the reliability and the cost of systems. This paper presents a new Particle Filter (PF) framework for lead-acid battery's RUL prediction by incorporating the battery's electrochemical model. An electrochem...