Journal of Advanced Computational Intelligence and Intelligent Informatics
Online ISSN : 1883-8014
Print ISSN : 1343-0130
ISSN-L : 1883-8014
Regular Papers
Estimation of SOC Based on LSTM-RNN and Design of Intelligent Equalization Charging System
Xi ChenKaoru HirotaYaping DaiZhiyang Jia
著者情報
ジャーナル オープンアクセス

2020 年 24 巻 7 号 p. 855-863

詳細
抄録

Lithium battery packs are the main driving energy source for electric vehicles. A battery pack equalization charging solution using a constant current source for variable rate charging is presented in this paper. The charging system consists of a main constant current source and independent auxiliary constant current sources. Auxiliary constant current sources are controlled by the battery management system (BMS), which can change the current rate of the corresponding single battery, and achieve full charging of each single cell in the series battery pack. At the same time, the state of charge (SOC) is regarded as time series data to establish a long short-term memory recurrent neural network (LSTM-RNN) model, and it is possible to obtain the single battery with lower capacity, so that the charging efficiency and battery pack consistency can be improved. The experimental results show that the open circuit voltage difference between the single cells is less than 50 mV after the charging of 20 strings of lithium battery packs by using this method, which achieve the purpose of equalization charging.

著者関連情報

この記事は最新の被引用情報を取得できません。

© 2020 Fuji Technology Press Ltd.
前の記事 次の記事
feedback
Top