A lithium battery equivalent circuit parameter identification method based on DNA coding multi-population particle swarm genetic algorithm

By combining a multi-population particle swarm genetic algorithm based on DNA encoding with the particle swarm algorithm, the problems of poor local search capability and slow convergence speed of genetic algorithms in the identification of equivalent circuit parameters of lithium batteries are solved, and higher identification accuracy and efficiency are achieved.

CN115994553BActive Publication Date: 2026-04-17ZHEJIANG UNIV +1
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Patent Information

Application Number
CN202211522403.3
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-11-30
Publication Date
2026-04-17
Estimated Expiration
2042-11-30

AI Technical Summary

Technical Problem

Existing genetic algorithms suffer from problems such as poor local search capability, slow convergence speed, rapid loss of individual diversity, and susceptibility to local optima and premature convergence in the identification of equivalent circuit parameters of lithium batteries, which limit the optimization efficiency and solution results.

Method used

A multi-population particle swarm genetic algorithm based on DNA encoding is adopted, which uses the four base symbols of DNA to represent the genetic information of individuals in the population. By combining multi-population genetic algorithm and particle swarm algorithm, the crossover and mutation probabilities of different populations and migration operations are used. The particle swarm algorithm of elite population is combined to perform local optimization, thereby improving the global and local search capabilities.

Benefits of technology

It improves the accuracy and efficiency of lithium battery equivalent circuit parameter identification, maintains population diversity, avoids getting trapped in local optima, enhances the algorithm's global optimization ability and evolutionary efficiency, and achieves higher fitting accuracy and lower computational cost.

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Abstract

This invention discloses a method for identifying lithium battery equivalent circuit parameters based on a multi-population particle swarm genetic algorithm using DNA encoding: (1) establishing a lithium battery equivalent circuit model with a well-defined structure; (2) obtaining dynamic current and voltage data of the lithium battery under different charging states using hybrid pulse power characteristic testing; (3) optimizing the parameter identification process in the lithium battery equivalent circuit model using a multi-population particle swarm genetic algorithm to obtain the optimal identification parameters; wherein, in step (3), the lithium battery equivalent circuit model obtains the estimated value of the battery terminal voltage at each dynamic moment by substituting the current parameter value and the dynamic current data at each moment in step (2); the fitness function in the multi-population particle swarm genetic algorithm is established based on the estimated value of the battery terminal voltage and the dynamic voltage data / measured voltage at the corresponding moment in step (2). This method has excellent identification effect on lithium battery equivalent circuit parameters.
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