Active cell balancing control strategy for parallel connected LiFePO4 batteries
Qays, Md Ohirul, Buswig, Yonis, Hossain, Md Liton, Rahman, Md Momtazur, Abu-Siada, Ahmed
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%.