Lithium-ion battery pack temperature prediction method, system, and storage medium

Abstract

The application provides a lithium ion battery pack temperature prediction method, system and storage medium, and the method comprises the following steps: obtaining historical operation data of a battery pack liquid cooling system, preprocessing the historical operation data to obtain an operation data set; constructing a thermal management model according to the operation data set, and obtaining a training residual sequence of the thermal management model; training a neural network model according to the operation data set and the training residual sequence, and optimizing parameters of the neural network model; combining the neural network model after parameter optimization and the thermal management model to obtain a battery pack temperature prediction model; obtaining to-be-tested operation data of the battery pack liquid cooling system, inputting the to-be-tested operation data into the battery pack temperature prediction model for temperature prediction, and obtaining a predicted temperature value. According to the application, the to-be-tested operation data is input into the battery pack temperature prediction model for temperature prediction, so that the battery temperature of the to-be-tested lithium ion battery pack can be effectively predicted, and the lithium ion battery pack temperature prediction efficiency is improved.

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