Estimation of SOC Based on LSTM-RNN and Design of Intelligent Equalization Charging System

Author:

Chen Xi,Hirota Kaoru,Dai Yaping,Jia Zhiyang, ,

Abstract

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.

Funder

National Talents Foundation

Natural Science Foundation of Beijing Municipality

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

Reference21 articles.

1. Y. Ma, P. Duan, Y. Sun et al., “Equalization of Lithium-ion Battery Pack based on Fuzzy Logic Control in Electric Vehicle,” IEEE Trans. on Industrial Electronics, Vol.65, No.8, pp. 6762-6771, 2018.

2. Q. Huang, H.-B. Yan, and R. Ling, “Design and Implementation of Non-dissipative Equalization Management Scheme for Series Connected Li-ion Battery Pack,” Computer Engineering, Vol.37, No.12, 2011 (in Chinese).

3. F. X. Cheng, X. Wang, and Y. Wang, “On the Balanced Charging Control Method for EV Lithium Battery,” Automotive Electronics, Vol.5, pp. 49-51, 2014 (in Chinese).

4. B. B. Qiu, Z. H. Wang, C. Li et al., “Fuzzy Control Strategy for Battery Equalization Charge Based on State of Charge,” J. of Power Supply, Vol.13, No.2, pp. 113-120, 2015 (in Chinese).

5. J. Q. Qin, F. Ran, Y. Ji et al., “A Fuzzy Control Based Equalization System with Clipping and Parallel Valley Filling,” Power Electronics, Vol.2, pp. 74-77, 2017 (in Chinese).

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