Active cell balancing control strategy for parallel connected LiFePO4 batteries

• Main Authors: Buswig, Yonis.M.Yonis, Md Ohirul, Qays, Md Liton, Hossain, Md Momtazur, Rahman, Ahmed, Abu-Siada
• Format: Article
• Language: English
• Published: China electric power research institute 2020
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://ir.unimas.my/id/eprint/31841/1/Active%20cell%20-%20Copy.pdf; http://ir.unimas.my/id/eprint/31841/; https://ieeexplore.ieee.org/abstract/document/9171672
• Institution: Universiti Malaysia Sarawak

While several recent studies have focused on eliminating the imbalance of energy stored in series-connected battery cells, not much attention has been given to balance the energy stored in parallel-connected battery cells. As such, this paper aims at presenting a new balancing approach for parallel LiFePO 4 battery cells. In this regards, 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 operation through DC/DC Buck-Boost converter. Simulation results reveal 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%.