Weighted Clustering Method for Retired Lithium-ion Batteries Screen under Different Operating Scenarios

With the extensive use of lithium-ion batteries, the world is facing the problem of large-scale retirement of batteries. The second-use of retired lithium-ion batteries can effectively extend the service life of the batteries, so the second-use has received the key attention of the industry. However, most of the existing battery screening methods in the second-use process are conducted without historical data, and there is a lack of thinking about the scenarios with historical data. At the same time, most of the existing methods only screen according to the performance of the battery, but ignore the needs of the battery application scenario. In view of the above problems, this paper proposes a method of weighted clustering method for retired lithium-ion batteries screen under different operating scenarios. First, the method assumes that the retired batteries are preliminarily screened and data filtered under the premise of historical data to reduce the impact of data fluctuations. Then, according to the application scenario of the battery, a screening method with feature weight is designed to improve the matching degree between the battery and the specific scenario. Finally, the validity of the proposed method is verified by the battery data tested in the laboratory.