Abstract: The flexible and efficient consistency screening technology for retired batteries is one of the key technologies that restrict the large-scale integrated application of retired batteries. In order to meet the retired batteries consistency screening requirements in different application scenes, this paper proposed a customized clustering screening method based on the retired batteries characteristics and intelligent optimization algorithms. Compared with the traditional method, the method in this paper firstly improved the flexibility of consistency screening of retired batteries by customizing multiple objective functions for service-oriented requirements based on retired battery characteristic parameters. Then, an improved genetic intelligent optimization screening strategy based on clustering ideas was proposed to realize the global optimization screening of retired battery samples. Finally, this paper analyzed and compared the clustering optimization results of the three objective functions to verify that the proposed method can effectively screen retired batteries in a targeted manner, which can facilitate in forming different types of batteries screening boundaries and realize the rapid judgment of the the battery to be tested.