IEEE - Institute of Electrical and Electronics Engineers, Inc. - Low-Cost Adaptive Lebesgue Sampling Particle Filtering Approach for Real-Time Li-Ion Battery Diagnosis and Prognosis

Author(s): Wuzhao Yan ; Bin Zhang ; Wanchun Dou ; Datong Liu ; Yu Peng
Sponsor(s): IEEE Robotics and Automation Society
Publisher: IEEE - Institute of Electrical and Electronics Engineers, Inc.
Volume: PP
Page(s): 1 - 11
ISSN (Paper): 1545-5955
ISSN (Online): 1558-3783
DOI: 10.1109/TASE.2017.2666202
Regular:

In the past decades, fault diagnosis and prognosis (FDP) approaches were developed in the Riemann sampling (RS) framework, in which samples are taken and algorithms are executed in periodic time... View More

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