articleTop 1% cited
Prognostics of lithium-ion batteries based on Dempster–Shafer theory and the Bayesian Monte Carlo method
Journal of Power Sources · 2011 · Vol. 196(23) · pp. 10314–10321
Wei He(Life Cycle Engineering (United States))Nicholas Williard(Life Cycle Engineering (United States))Michael Osterman(Life Cycle Engineering (United States))Michael Pecht✉(University of Maryland, College Park)
Advanced Battery Technologies ResearchReliability and Maintenance OptimizationAdvancements in Battery MaterialsPrognosticsMonte Carlo methodBattery (electricity)Bayesian probabilityParticle filterDempster–Shafer theoryComputer scienceState of healthLithium (medication)Reliability engineering
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References
Issue and challenges facing rechargeable thin film lithium batteries
Materials Research Bulletin · 2007 · 593 citations
Ageing mechanisms in lithium-ion batteries
Journal of Power Sources · 2005 · 3,716 citations
Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework
IEEE Transactions on Instrumentation and Measurement · 2008 · 802 citations
Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs
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A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
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