Yinjiao Xing, Qiang Miao, K.-L. Tsui and Michael Pecht
Center for
Prognostics
and
System
Health
Management,
City
University
of
Hong
Kong,
Hong
Kong
Dept.
of
Manufacturing
Engineering
and
Engineering
Management, City
University
of Hong
Kong
Hong
Kong
Center for
Advanced
Life
Cycle
Engineering
(CALCE),
University
of
Maryland,
College
Park
Maryland,
USA
Abstract:
Health monitoring is used to analyze and predict the battery health status. However, no matter what health monitoring methods and parameters are, a major aim is to improve the battery reliability through surveillance and prognostics. Hence, the latest known methods of state estimation and life prediction based on battery health monitoring are discussed in this paper. Through comparing their characteristics respectively, a prognostics-based fusion technique is proposed that combines physics-of-failure (PoF) with data-driven technology. The fusion approach not only investigates battery failure mechanism caused by environmental and internal characteristics, but also assesses parameters with aid of real-time health monitoring. The specific method is presented to realize the estimation on remaining useful life (RUL) of batteries.Complete article is available from the publisher and to the CALCE Consortium Members.
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