Remaining Useful Performance Analysis of
Batteries
Wei He
Nicholas Williard
Michael Osterman
Michael Pecht
Abstract:
A method for remaining useful performance (RUP)
analysis for lithium-ion batteries is presented using Dempster-
Shafer theory (DST) and Bayesian Monte Carlo (BMC). First, an
empirical model is developed, which can provide a good fit to the
battery fade data. Then, the parameters of the empirical model
are initialized by combining sets of training data based on DST.
When data become available through battery monitoring, the
model parameters are updated by the BMC to manage the
uncertainties in the degradation process. Once the model
converges to the observed degradation process, it can be
propagated to the acceptable performance threshold to predict
the RUP of batteries. The proposed approach is validated using
experimental data.
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