Battery state of health modeling and remaining useful life prediction through time series model

•A model considering stochasticity instead of deterministic degradation shape.•Predict degradation by constructing segments iteratively with autoregressive nature.•Produce remaining useful life confidence intervals from bootstrap distribution.•The proposed model is applicable to two different lithium-ion batteries.•Comparison shows the proposed model can predict better when plunge is not present.