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Low-Cost Adaptive Lebesgue Sampling Particle Filtering Approach for Real-Time Li-Ion Battery Diagnosis and Prognosis

contributor authorWuzhao Yan
contributor authorBin Zhang
contributor authorWanchun Dou
contributor authorDatong Liu
contributor authorYu Peng
date accessioned2020-03-15T10:20:39Z
date available2020-03-15T10:20:39Z
date issued2017
identifier others9CALVAf11x1pNZkLY72b_GAv1aCOrp0y44p7oeHmaC4FjVfae.pdf
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/1918460?locale-attribute=fa&show=full
formatgeneral
languageEnglish
titleLow-Cost Adaptive Lebesgue Sampling Particle Filtering Approach for Real-Time Li-Ion Battery Diagnosis and Prognosis
typeJournal Paper
contenttypeFulltext
contenttypeFulltext
identifier padid13415121
identifier doi10.1109/TASE.2017.2666202
journal titleIEEE Transactions on Automation Science and Engineering
coverageAcademic
pages1-11
filesize2684928
citations2


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