Abstract: Aiming at the problems of inconsistent initial capacity and complex selection and reorganization of retired power batteries' echelon utilization in power system and other fields, a stepped screening method considering the static and dynamic characteristics of retired power battery modules (BMs) is proposed. First, the correlation characteristics among parameters such as terminal voltage, state of charge (SOC), state of health (SOH) and cycle numbers of retired power BMs is constructed. Taking battery module's internal resistance and residual capacity as characterization parameters, K-medoids clustering method based on density weighted canopy is adopted to screen BMs with similar external characteristics. Secondly, taking the SOH dynamic consistency characteristic curve as the characterization object, the BMs are further screened. Finally, the non-parametric Bootstrap probability method is used to analyze the confidence interval of SOH estimation of retired power BMs under static-dynamic screening. The screening accuracy of power battery modules is evaluated. The results show that the method proposed can improve the screening accuracy of battery modules by at least 6.2%. It lays a theoretical foundation for large-scale screening and echelon utilization of retired power batteries.