Research on lithium-ion battery life prediction method based on improved bird swarm algorithm least squares support vector machine

With the wide application of lithium-ion batteries, life prediction and health management have become a hot issue nowadays. Life prediction of lithium batteries is of great significance to the stable operation of battery management system. Least squares support vector machine (LSSVM) model id used to predict the residual life of lithium ion batteries, and bird swarm optimization algorithm (BSA) is used头optimize the parameters of LSSVM. In order to improve the global search ability of BSA, the BSA is improved and an improved bird swarm algorithm (IBSA) is proposed. Finally, the least squares support vector machine (LSSVM) is optimized by using IBSA, and the IBSA-LSSVM prediction model is established to predict the life of lithium-ion batteries. The test results show that IBSA-LSSVM model has good prediction effect and stability.


(from magazine Electrotechnical Application5/2020 on theoretical analysis.)


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