The invention relates to a method for remain useful life prognostic of a
lithium ion battery with a model active updating strategy. According to a
time series obtained through a
voltage range of a
discharge curve, conversion is conducted so that an equivalent
discharge difference series obtained by
discharge circulation at each time can be obtained, and therefore a
health index time series of the
ion battery is obtained; according to correspondence of a discharge
voltage series and a
time series, prognostic is conducted on the
health index series to determine the remain useful life of the battery. Sampling entropy characteristic extraction and modeling are conducted on a
charge voltage curve so that a relationship between a complete and accurate charge / discharge process and a battery
performance index can be provided. On the basis of a
performance index model, a short-term time series prognostic result is continuously updated to a known
performance index data series and
correlation analysis is conducted. According to the difference of the correlation degrees, retraining is conducted in the mode of
training set expansion. The method is different from an existing iteration updating draining method, the
prognostic model is updated dynamically, and therefore the prognostic precision is improved.