Intelligent method and system for dynamic parameter weight adjustment in battery cell sorting process

By collecting and analyzing battery cell data in real time, and using natural heuristic optimization algorithm to dynamically adjust the weight of battery cell sorting parameters, the problem of inability to flexibly adjust the weight of dynamic parameters in the existing technology is solved, and the accuracy and reliability of battery cell sorting are improved.

CN119902476APending Publication Date: 2025-04-29BEIJING XUNCHAO TECH CO LTD
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Patent Information

Application Number
CN202510369809.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-27
Publication Date
2025-04-29

AI Technical Summary

Technical Problem

The prior art cannot flexibly adjust the dynamic parameter weights during the battery cell sorting process, resulting in a decrease in the sorting effect and being unable to adapt to new special situations or changes in data distribution.

Method used

By deploying sensors in electric vehicles and charging stations, collecting battery cell data in real time, cleaning and normalizing, correlation analysis obtains battery cell sorting parameters, assigning initial weights to each parameter, and using natural heuristic optimization algorithm to optimize the weight vector, and dynamically adjust the parameter weights.

Benefits of technology

It realizes improving the performance matching of the battery cell in complex usage scenarios, avoiding the performance failure caused by unreasonable parameter weights, ensuring the accuracy and reliability of sorting, and improving the overall quality of battery cell sorting.

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Abstract

The invention belongs to the technical field of battery sorting, and discloses an intelligent method and system for dynamic parameter weight adjustment in the battery cell sorting process. The method comprises the steps of deploying sensors in an electric vehicle and a charging station, and collecting cell data in real time; performing cleaning and normalization processing on the battery cell data to obtain standard battery cell data; performing correlation analysis on the standard battery cell data to obtain battery cell sorting parameters; an initial weight is given to each cell sorting parameter; splicing the initial weights of the cell sorting parameters as an initial weight vector, and optimizing the initial weight vector based on a natural heuristic optimization algorithm to obtain the optimal weight of the cell sorting parameters; according to the method, the weight can be dynamically updated according to real-time monitoring data, the sorting accuracy is always ensured, the overall quality and reliability of battery cell sorting are greatly improved, and a solid guarantee is provided for efficient and stable operation of a two-wheeled vehicle and a three-wheeled vehicle.
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