Lithium-ion battery modeling based on Big Data

Abstract

Battery is the bottleneck technology of electric vehicles. The complex chemical reactions inside the battery are difficult to monitor directly. The establishment of a precise mathematical model for the battery is of great significance in ensuring the secure and stable operation of the battery management system. First of all, a data cleaning method based on machine learning is put forward, which is applicable to the characteristics of big data from batteries in electric vehicles. Secondly, this paper establishes a lithium-ion battery model based on deep learning algorithm and the error of model based on different algorithms is compared. The data of electric buses are used for validating the effectiveness of the model. The result shows that the data cleaning method achieves good results, in the case of the terminal voltage missing, the mean absolute percentage error of filling is within 4%, and the battery modeling method in this paper is able to simulate the battery characteristics accurately, and the mean absolute percentage error of the terminal voltage estimation is within 2.5%.