The accurate estimation of the state of charge (SOC) of a battery is increasingly important in the context of the wide application of batteries. However，it is difficult to build accurate physical models，and the use of pure datadriven methods is prone to overfitting problems due to individual differences of batteries. To solve these problems，propose a method based on belief rule base (BRB) to estimate SOC of lithium battery. This method allows experts to overcome the overfitting problem of datadriven methods through empirical knowledge and the inaccuracy of expert knowledge through parameter training. A lithium iron phosphate (LiFePO-4) battery is taken as an example to verify the proposed method，and the results are compared with those of the neural network. The results show that this method has high accuracy in SOC estimation，the estimated error is not more than 10%，and can overcome the overfitting problem of traditional neural network methods.