Abstract: In this work, a battery’s state of health(SOH) estimation method is developed with capacity and energy as characterization parameters. Two methods are used to estimate the SOH. First, the metabolic grey algorithm(MGA) is used to predict the battery capacity and energy by insetting the original battery capacity and energy sequence directly. Second, the original model parameters are imput, the parameters of simplified electrochemical model(SEM) are predicted by using grey prediction algorithm, the predicted parameter values are brought back to the model, the battery terminal voltage curve is fit, and the battery capacity and energy are obtained by integration method. Aiming at the decay rate and estimation accuracy of the two characterization parameters, and a comprehensive battery health state estimation method based on data-model hybrid drive is developed to realize the accurate prediction of battery SOH.