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Active cell balancing control strategy for parallelly connected LiFePO4 batteries

机译:平行连接LiFepo4电池的主动细胞平衡控制策略

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摘要

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%.
机译:虽然最近的几项研究专注于消除串联电池单元中存储的能量的不平衡,但很少地注意到平衡存储在并联电池单元中的能量。因此,本文旨在提出一种用于并行LiFePO4电池单元的新平衡方法。在这方面,采用基于背面的神经网络(BPNN)技术来开发电池管理系统(BMS),其可以评估所有单元的充电状态并通过DC / DC降压 - 升压转换器控制其操作。仿真结果证明了所提出的方法在平衡存储在并联电池单元中的能量的有效性,其中发现电荷状态(SOC)估计误差仅为1.15%。

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