Decision tree-based screening method for decommissioned power batteries of new energy electric vehicles

Abstract

Based on the decision tree-based screening method of retired power batteries for new energy electric vehicles, first determine the grade types of retired power batteries, use each grade type as a leaf node, and calculate the information entropy of the retired power battery data sample D; then, select the retired power battery Characteristic properties of the battery A i , respectively calculate each A i The amount of information entropy information gain IG(D,A i ), intrinsic value IV(D,A i ), information gain rate GR(D,A i ); Finally, choose the information gain rate GR(D,A i ) the larger A i As the root node; use the same method to select the leaf node in the decision tree. Therefore, an intelligent classification decision tree for decommissioned power batteries of new energy electric vehicles can be obtained. This method helps to improve the screening efficiency of decommissioned power batteries. The decommissioned power batteries are graded and used in grid energy storage power stations, new energy power generation and other fields, which can prolong the service life of power batteries, improve the economic benefits of power batteries, and reduce the impact of decommissioned power batteries on the environment.

Description

technical field [0001] The invention relates to the technical field of grade screening of power batteries, in particular to the grade screening technology of decommissioned power batteries of new energy electric vehicles. Background technique [0002] In recent years, the issues of energy conservation, emission reduction and environmental protection have drawn great attention from the international community. New energy electric vehicles help to reduce fuel consumption and exhaust emissions, and are an important development direction of the automobile industry. Thanks to the country's strong support for the new energy vehicle industry in the early stage, the production and sales of new energy vehicles have also increased significantly, and the competitiveness of the new energy vehicle market has increased significantly. However, behind the rapid development of new energy vehicles, there are still some outstanding problems. When the power battery capacity decays to 80% of th...

AI Technical Summary

Problems solved by technology

[0004] At present, the existing grade screening technology is mainly the traditional Full Charge-Discharge (CFD) screening method, but this screening method has the disadvantages of low screening efficiency and large energy consumption.

The screening methods for decommissioned power batteries can be divided into single-parameter screening, multi-parameter screening, and characteristic curve screening according to different screening indicators. These methods have defects such as incomplete characterization of the overall performance of the battery, low screening efficiency, and difficulty in obtaining characteristic curves.

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