Journal of Power Sources 196 (2011) 10314– 10321

Prognostics of lithium-ion batteries based on Dempster–Shafer theory and the
Bayesian Monte Carlo method

Wei He, Nicholas Williard, Michael Osterman, Michael Pecht
Center for Advanced Life Cycle Engineering, University of Maryland, College Park, MD 20742, USA


A new method for state of health (SOH) and remaining useful life (RUL) estimations for lithium-ion batteries using Dempster–Shafer theory (DST) and the Bayesian Monte Carlo (BMC) method is proposed. In this work, an empirical model based on the physical degradation behaviour of lithium-ion batteries is developed. Model parameters are initialized by combining sets of training data based on DST. BMC is then used to update the model parameters and predict the RUL based on available data through battery capacity monitoring. As more data become available, the accuracy of the model in predicting RUL improves. Two case studies demonstrating this approach are presented.d to manage the supply chain problems be avoided if military and aerospace adopted a disposable electronics approach?

Complete article is available from the publisher and to the CALCE consortium members.

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