Electric forklift lithium ion battery health state prediction method based on LSTM-FFNN

Abstract

The invention provides an electric forklift lithium ion battery health state prediction method based on LSTM-FFNN, and mainly solves the problems that in the prior art, a prediction method is large incalculated amount and low in prediction result precision. Data required for model training is reduced, and the lithium battery health state prediction precision is improved. The method comprises thefollowing steps: establishing a time scale parameter prediction model based on LSTM to predict change of time scale parameter open-circuit voltage V in the discharge process; extracting the time Tminwhen the cycle scale parameter discharges to the minimum voltage from the open-circuit voltage V of the time scale parameter prediction model; and establishing a cycle scale parameter prediction modelbased on the FFNN to predict the lithium battery capacity C so as to obtain a lithium battery health state prediction value SOH. According to the method, the prediction capability of the LSTM for thelong time sequence and the algorithm simplicity of the FFNN are combined, prediction from the time scale parameter to the cycle scale parameter is realized, the data required for training the model is reduced, and the precision of predicting the health state of the lithium battery is improved.

Description

technical field [0001] The invention relates to the technical field of batteries, in particular to a battery health state prediction method. Background technique [0002] Lithium-ion battery is a kind of rechargeable battery. The positive and negative electrodes are generally made of materials containing lithium elements. During the charge and discharge process, lithium ions are extracted from one electrode material, and then moved and embedded in the other electrode material. Lithium-ion batteries have been widely used in various fields due to their high operating voltage, long cycle life, high energy density, and low self-discharge rate. Under the continuous charge and discharge cycle, the material structure of the lithium-ion battery gradually changes under the condition of continuous intercalation and extraction of lithium ions, and more and more defects appear, and the electrochemical performance of the lithium-ion battery gradually declines. . Lithium-ion batteries c...

AI Technical Summary

Problems solved by technology

Lithium-ion batteries cannot provide stable energy after reaching the maximum life, and need to be maintained and replaced in time. If they continue to be used, they may cause economic losses and even cause important safety issues.

[0003] Lithium-ion batteries are an important power source for electric forklifts. In the process of continuous charging and discharging, the performance of the batteries decreases and the capacity decays. After reaching the maximum life, lithium batteries will not be able to provide stable energy for electric forklifts. Continued use will easily lead to economic losses. , and even lead to serious safety problems, and the current monitoring method for the health status of electric forklift lithium batteries has low accuracy and cannot meet the actual industrial needs

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