Active cell balancing control strategy for parallelly connected LiFePO4 batteries
Abstract
© 2015 CSEE. While several recent studies have focused on eliminating the imbalance of energy stored in series-connected battery cells, very little attention has been given to balancing the energy stored in parallel-connected battery cells. As such, this paper aims at presenting a new balancing approach for parallel LiFePO4 battery cells. In this regard, a Backpropagation Neural Network (BPNN) based technique is employed to develop a Battery Management System (BMS) that can assess the charging status of all cells and control its operations through a DC/DC Buck-Boost converter. Simulation results demonstrate the effectiveness of the proposed approach in balancing the energy stored in parallel-connected battery cells in which the state of charge (SoC) estimation error is found to be only 1.15%.
RAS ID
38771
Document Type
Journal Article
Date of Publication
2020
Volume
7
Issue
1
Funding Information
Ministry of Higher Education, Malaysia
School
Electron Science Research Institute / School of Engineering
Copyright
free_to_read
Publisher
Chinese Society of Electrical Engineering
Comments
Qays, M. O., Buswig, Y., Hossain, M. L., Rahman, M. M., & Abu-Siada, A. (2021). Active cell balancing control strategy for parallelly connected LiFePO4 batteries. CSEE Journal of Power and Energy Systems, 7(1), 86-92. https://doi.org/10.17775/CSEEJPES.2020.00740