Remaining Useful Life Estimation of Lithium-ion Batteries based on a new Capacity Degradation model

This paper presents a method for remaining useful life (RUL) estimation of lithium-ion batteries using Particle Filtering approach. Firstly, a new empirical model for capacity degradation has been developed based on experimentally obtained capacity fade data. Next, the obtained model is used in a particle filtering (PF) framework to make end of life predictions at various stages of its Iifecycle. Finally, the predictions were compared with experimental results using coin cell data and quite good matches obtained. From the results it can be further observed that as more data becomes available, the prediction accuracy of the model improves. The proposed framework provides a systematic way for monitoring the battery capacity degradation in real time.