A method for predicting the health status of lithium-ion batteries in electric forklifts based on lstm-ffnn

Abstract

The invention mainly solves the problem that the prediction method in the prior art has a large amount of calculation and low accuracy of the prediction result; it provides a LSTM-FFNN-based electric forklift lithium-ion battery health state prediction method, which reduces the data required for training the model and improves the lithium ion battery state. The accuracy of battery state of health predictions. It includes the following steps: establishing a time-scale parameter prediction model based on LSTM to predict the change of the time-scale parameter open-circuit voltage V during the discharge process; extracting the cycle-scale parameter discharge time T from the open-circuit voltage V of the time-scale parameter prediction model to the minimum voltage min ; Establish a cycle-scale parameter prediction model based on FFNN to predict the lithium battery capacity C, thereby obtaining the predicted value SOH of the lithium battery state of health. Combining the prediction ability of LSTM for long-term series and the algorithm simplicity of FFNN, the prediction from time-scale parameters to cycle-scale parameters is realized, which reduces the data required for training the model and improves the accuracy of lithium battery health state prediction.

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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