Electric vehicle battery health state and residual life evaluation method based on charging network

Abstract

The invention relates to an electric vehicle battery health state and residual life evaluation method based on a charging network, and the method comprises the steps: firstly, obtaining various state parameters of battery charging on line when an electric vehicle is charged in the charging network, and storing the state parameters in a database; secondly, dividing data in the database into historical data and real-time data, and preprocessing the historical data and the real-time data; then, establishing a target battery health factor (HI) standard, obtaining battery historical HI data from the preprocessed historical data, and obtaining battery real-time HI data from the preprocessed real-time data; then, designing a CNN-BiLSTM-AM hybrid network model, fully learning historical HI data of the battery, and constructing a prediction model of the battery capacity of the electric vehicle; then, an evaluation standard of model prediction precision is formulated and is used for judging the accuracy of model prediction; and finally, the trained CNN-BiLSTM-AM hybrid network model is applied to online charging monitoring, and battery health state and residual life evaluation of the electric vehicle is realized by using battery real-time HI data.

Description

technical field [0001] The invention belongs to the field of battery health state and remaining life prediction field, in particular to a method for evaluating the state of health and remaining life of an electric vehicle battery based on a charging network. Background technique [0002] New energy electric vehicles use electric energy as the main energy source, which is conducive to alleviating the oil energy crisis and reducing carbon emissions. With the rapid development of electric vehicles, the health status and remaining service life of electric vehicle batteries are closely related to the performance of new energy vehicles. It is particularly important to improve the traceability management system for the recycling and utilization of new energy vehicle power batteries. Therefore, online monitoring of electric vehicle battery health status and service life assessment, and battery health status assessment before the end of electric vehicle battery life are very importan...

AI Technical Summary

Problems solved by technology

[0004] In related technologies, battery SOH is often predicted from the complete charging and discharging process of electric vehicles. However, since the discharge data of electric vehicles can be monitored in real time, it is difficult for practical application, but the method of obtaining charging data of electric vehicles from the charging network for prediction is relatively relatively few

Images